775 Econometrics Jobs - Page 4

Company Description CrystalVoxx is a healthcare econometrics company providing integrated healthcare solutions, including Medical Billing and Coding Services. These services encompass Provider Insurance Credentialing, Clearing House configuration, EDI Enrollment, ERA & EFT Enrollment, Patients Insurance Benefits Verification, Claims Scrubbing, Charge Entry, Payment Posting, and AR Recovery & Denial Management. CrystalVoxx's unique workflow and advanced analytics ensure that no revenue is left uncollected. Role Description This is a full-time on-site role for an AR Caller - Medical Billing based in Ahmedabad. The AR Caller is responsible for handling unpaid claims by performing tasks such as insurance follow-up, rebilling, sending appeals, and reprocessing claims via phone. Daily responsibilities include calling insurance companies to check claim statuses, addressing denials, and ensuring that payments are accurately posted. Maintaining accurate patient demographic data and verifying insurance benefits are also part of the job. Qualifications Experience in insurance follow-up and managing unpaid claims Skills in rebilling, sending appeals, and reprocessing claims Proficiency in handling insurance benefits verification and demographic entry Familiarity with Medical Billing and Coding processes Strong communication and customer service skills Ability to work accurately and efficiently in a high-paced environment Experience in using Medical Billing software and tools Understanding of healthcare regulations and compliance standards Previous experience in a similar role is preferred Bachelor's degree in a related field or equivalent work experience

Qualifications Master’s in Economics / Development Economics or MBA in Finance/Economics Key Responsibilities Use econometrics and modelling to evaluate policies, GDP trends, and regional competitiveness. Conduct sectoral research, feasibility studies, and investment climate assessments. Analyze data using tools like SPSS, Stata, R, and Excel; present insights using PowerPoint. Translate complex data into clear, actionable recommendations for policy and investment. Map investment opportunities across sectors and regions, with a focus on district-level analysis. Coordinate with industry, government, and institutional stakeholders to drive investment pipelines. Prepare investment strategies, pitch decks, and policy briefs. Support investment facilitation and contribute to economic development initiatives. Required Skills Strong data analysis and research capabilities. Familiarity with economic development and investment promotion frameworks. Excellent written and verbal communication. Proficient in research tools and Microsoft Office Suite. Ability to engage with senior stakeholders and work in a dynamic environment. Skills: spss,research tools,investment,r,microsoft office suite,data analysis,familiarity with economic development frameworks,modelling,stata,investment strategies,economics,government,investment facilitation,investment promotion frameworks,data presentation,research capabilities,excel,stakeholder engagement,investment promotion,written communication,econometrics,powerpoint,verbal communication,gdp trends

At Takeda, we are guided by our purpose of creating better health for people and a brighter future for the world. Every corporate function plays a role in making sure we — as a Takeda team — can discover and deliver life-transforming treatments, guided by our commitment to patients, our people and the planet. People join Takeda because they share in our purpose. And they stay because we’re committed to an inclusive, safe and empowering work environment that offers exceptional experiences and opportunities for everyone to pursue their own ambitions. Job ID R0158759 Date posted 07/24/2025 Location Bengaluru, Karnataka I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’sPrivacy Noticeand Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description The Future Begins Here At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet. Bengaluru, the city, which is India’s epicenter of Innovation, has been selected to be home to Takeda’s recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement. At Takeda’s ICC we Unite in Diversity Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team. The Opportunity: The Data Enginee r will work directly with architects and product owners on the delivery of data pipelines and platforms for structured and unstructured data as part of a transformational data program. This data program will include an integrated data flow with end-to end control of data, internalization of numerous systems and processes, broad enablement of automation and near-time data access, efficient data review and query, and enablement of disruptive technologies for next-generation trial designs and insight derivation. We are primarily looking for people who love taking complex data and making it easy to use. As a Data Engineer you will Provide leadership to develop and execute highly complex and large-scale data structures and pipelines to organize, collect and standardize data to generate insights and addresses reporting needs. Interpret and integrate advanced techniques to ingest structured and unstructured data across complex ecosystem Delivery & Business Accountabilities Build and maintain technical solutions required for optimal ingestion, transformation, and loading of data from a wide variety of data sources and large, complex data sets with a focus on clinical and operational data Develop data profiling and data quality methodologies and embed them into the processes involved in transforming data across the systems. Manages and influences the data pipeline and analysis approaches, uses different technologies, big data preparations, programming and loading as well as initial exploration in the process of searching and finding data patterns. Uses data science input and requests, translates these from data exploration - large record (billions) and unstructured data sets - to mathematic algorithms and uses various tooling from programming languages to new tools (artificial and machine learning) to find data patterns, build and optimize models. Leads and implements ongoing tests in the search for solutions in data modelling, collects and prepares the training of data, tunes the data, optimizes algorithm implementations to test, scale, and deploy future models. Conducts and facilitates analytical assessment conceptualizing business needs and translates them into analytical opportunities. Leads the development of technical roadmaps and approaches for data analyses to find patterns, to design data models, to scale the model to a managed production environment within the current or a technical landscape to develop. Influences and manages data exploration from analysis to scalable models, works independently and decides quickly on transfers in complex data analysis and modelling. Skills and Qualifications: Bachelor’s degree or higher in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Econometrics or information sciences such as business analytics or informatics 5+ years of experience working in data engineering role in an enterprise environment Strong experience with ETL/ELT design and implementations in the context of large, disparate and complex datasets Demonstrated experience with a variety of relational database and data warehousing technology such as AWS Redshift, Athena, RDS, BigQuery Demonstrated experience with big data processing systems and distributed computing technology such as Databricks, Spark, Sagemaker, Kafka, Tidal/Airflow etc. Demonstrated experience with DevOps tools such as GitLab, Terraform, Ansible, Chef etc. Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space Solution-oriented enabler mindset Prior experience with Data Engineering projects and teams at an Enterprise level Preferred : Understanding or Application of Machine Learning and / or Deep Learning Significant experience in an analytical role in the healthcare industry preferred WHAT TAKEDA ICC INDIA CAN OFFER YOU: Takeda is certified as a Top Employer, not only in India, but also globally. No investment we make pays greater dividends than taking good care of our people. At Takeda, you take the lead on building and shaping your own career. Joining the ICC in Bengaluru will give you access to high-end technology, continuous training and a diverse and inclusive network of colleagues who will support your career growth. BENEFITS: It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are: Competitive Salary + Performance Annual Bonus Flexible work environment, including hybrid working Comprehensive Healthcare Insurance Plans for self, spouse, and children Group Term Life Insurance and Group Accident Insurance programs. Employee Assistance Program Broad Variety of learning platforms Diversity, Equity, and Inclusion Programs Reimbursements – Home Internet & Mobile Phone Employee Referral Program Leaves – Paternity Leave (4 Weeks), Maternity Leave (up to 26 weeks), Bereavement Leave (5 days) ABOUT ICC IN TAKEDA: Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day. As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization. #Li-Hybrid Locations IND - Bengaluru Worker Type Employee Worker Sub-Type Regular Time Type Full time

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY's Financial Services Office (FSO) is a unique, industry-focused business unit that provides a broad range of integrated services leveraging deep industry experience with strong functional capability and product knowledge. The FSO practice offers integrated advisory services to financial institutions and other capital markets participants, including commercial banks, investment banks, broker-dealers, asset managers, insurance and energy trading companies, and Corporate Treasury functions of leading Fortune 500 Companies. The service offerings include market, credit, and operational risk management, regulatory advisory, quantitative advisory, technology enablement, and more. Within EY's FSO Advisory Practice, the Financial Services Risk Management (FSRM) group provides solutions to help clients identify, measure, manage, and monitor market, credit, operational, and regulatory risks associated with trading, asset-liability management, and capital markets activities. The Credit Risk (CR) team within FSRM assists clients in designing and implementing strategic and functional changes across risk management within banking book portfolios of large domestic and global financial institutions. Key Responsibilities: - Demonstrate deep technical capabilities and industry knowledge of financial products, particularly lending products. - Stay informed about market trends and demands in the financial services sector and issues faced by clients. - Monitor progress, manage risk, and communicate effectively with key stakeholders. - Mentor junior consultants and review tasks completed by them. - Work on projects involving model audits, validation, and development activities. Qualifications, Certifications, and Education: Must-have: - Postgraduate degree in accounting, finance, economics, statistics, or related field with at least 3 years of related work experience. - Understanding of climate risk models, ECL, stress testing, and regulatory requirements related to credit risk. - Knowledge of Credit Risk and Risk Analytics techniques. - Hands-on experience in data preparation, manipulation, and consolidation. - Strong documentation skills and ability to summarize key details effectively. - Proficiency in statistics, econometrics, and technical skills in Advanced Python, SAS, SQL, R, and Excel. Good-to-have: - Certifications such as FRM, CFA, PRM, SCR. - Experience in Data/Business Intelligence Reporting and knowledge of Machine Learning models. - Willingness to travel and previous project management experience. EY exists to build a better working world, creating long-term value for clients, people, and society while building trust in capital markets. EY teams across 150 countries provide trust through assurance and help clients grow, transform, and operate in various sectors like assurance, consulting, law, strategy, tax, and transactions, addressing complex issues globally.,

The Risk Analytics, Modeling and Validation role involves the development, enhancement, and validation of methods for measuring and analyzing all types of risks, including market, credit, and operational. You will be responsible for developing, enhancing, and validating models for measuring obligor credit risk, early warning tools for monitoring credit risk of corporate or consumer customers, and conducting Loss Given Default studies. Additionally, you will develop and maintain key risk parameters such as default and rating migration data, usage given default data, and transition matrices. Your role is vital to the company as it provides a scientific and systematic approach to assessing and mitigating risks, ensuring the company's financial stability, protecting its assets, and supporting its overall business strategy. As a Model Validator, your responsibilities will include performing model validations, annual model reviews, ongoing monitoring reviews, and model limitation remediation reviews for one or more model/product types under the supervision of a Validation Lead. You will provide effective challenge to the model development process, evaluate testing approaches and results, assess ongoing performance monitoring of models, and contribute to regulatory and internal audit related responses. Collaboration with other teams within Risk and the Business will be essential to facilitate compliance with policies, procedures, and guidance. You are expected to be an enthusiastic and early adopter of change, demonstrating curiosity in seeking new ways to overcome challenges and actively applying learning from failures. You will be responsible for challenging yourself and others to communicate alternative views, acting as a change catalyst by identifying where new ideas could benefit the organization, and proactively seeking to understand and act in alignment with organizational decisions. Prioritizing highest-priority work aligned to business goals, streamlining work processes, and taking personal accountability for managing potential risks are also key aspects of this role. The ideal candidate for this role will have 5-8 years of experience in Quantitative Finance, Risk management, Analytics, Model Development, or Model Validation. Strong partnership and teamwork skills, along with the ability to formulate findings clearly and concisely, are essential. Good analytical, creative thinking, and problem-solving abilities are required, as well as proficiency in programming languages like Python, MATLAB, C/C++/C#, VBA, or other coding languages as needed. Knowledge of financial markets and products, qualitative or quantitative model risk management experience, and extensive experience in data analysis and interpretation are preferred qualifications. A Master's degree in a relevant field is required for this position. Strong technical skills in time series analysis, statistics, and econometrics, along with excellent communication, diplomacy, and problem-solving skills, are necessary. The ability to work effectively in a team and independently, manage multiple tasks and deadlines, and identify inconsistencies in data or results to define business issues are also crucial for success in this role. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, please review Accessibility at Citi. View Citis EEO Policy Statement and the Know Your Rights poster for more information.,

The Company Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do and they push us to ensure we take care of ourselves, each other, and our communities. Job Description: Your way to impact Your day to day Build, enhance, and document CECL/IFRS9-compliant loss prediction models, leveraging PD/EAD/LGD frameworks and vintage loss rate methodologies. Conduct rigorous model performance testing, stress testing, and scenario analysis to ensure models are robust and regulatory-compliant. Collaborate cross-functionally with implementation, finance, accounting, risk, and external stakeholders to align on model outputs, definitions, and business needs. Clearly communicate analytic insights and model results to senior leadership, and provide expert support for regulatory exams and audit reviews. What do you need to bring Advanced degree in a quantitative discipline (e.g., statistics, mathematics, data science, computer science, engineering, or related field). Deep expertise in statistical modeling, machine learning, or econometrics applied to credit risk, knowledge and familiarity of CECL and IFRS9 regulatory requirements and modeling best practices is a plus. Strong technical skills working with large datasets using SQL, Python, R, or similar tools; experience with cloud-based platforms such as GCP is highly desirable. 5+ years of hands-on experience developing consumer or small business credit risk models, preferably within a CECL/IFRS9 framework. Excellent communication and collaboration skills, with strong business judgment and a passion for data-driven problem solving. Our Benefits: Who We Are: To learn more about our culture and community visit https://about.pypl.com/who-we-are/default.aspx Commitment to Diversity and Inclusion Any general requests for consideration of your skills, please Join our Talent Community. We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.,

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? The position is responsible for managing credit risk Case setup, communications and FRP strategies for Consumer, SBS portfolio for the International markets. The role would specifically have direct functional responsibility for: Case Setup: Strategy to determine case setup strategies for further collection activities. Additionally partner with GSG to design and optimize treatment and collection strategies (e.g. how to collect a past due payment) Credit Communications: Design and own E2E Credit Notification strategies for both International Consumer & SBS portfolios NFC: Devise optimal No-further-charge strategies on CMs with a credit concern Collaborate closely with CCOs, Decision science, Credit operations, Compliance and Finance to deliver favorable business outcomes Minimum Qualifications Demonstrated experience driving and implementing credit risk management strategies Strong analytical acumen and problem solving skills Rigorous and analytical approach to problem-solving, decision-making, and prioritization Intellectual curiosity and learning agility needed to explore and evaluate new ideas Preferred Qualifications Advanced degree in statistics, econometrics, operations research, mathematics, computer science, engineering, or a related quantitative field of study We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? The position is responsible for managing credit risk Case setup, communications and FRP strategies for Consumer, SBS portfolio for the International markets. The role would specifically have direct functional responsibility for: Case Setup: Strategy to determine case setup strategies for further collection activities. Additionally partner with GSG to design and optimize treatment and collection strategies (e.g. how to collect a past due payment) Credit Communications: Design and own E2E Credit Notification strategies for both International Consumer & SBS portfolios NFC: Devise optimal No-further-charge strategies on CMs with a credit concern Collaborate closely with CCOs, Decision science, Credit operations, Compliance and Finance to deliver favorable business outcomes Minimum Qualifications Demonstrated experience driving and implementing credit risk management strategies Strong analytical acumen and problem solving skills Rigorous and analytical approach to problem-solving, decision-making, and prioritization Intellectual curiosity and learning agility needed to explore and evaluate new ideas Preferred Qualifications Advanced degree in statistics, econometrics, operations research, mathematics, computer science, engineering, or a related quantitative field of study We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Associate Product Specialist Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. ________________________________________ Overview The Services organization is a key differentiator for Mastercard, providing cutting-edge services that help our customers grow. Focused on thinking big and scaling fast around the globe, this agile team is responsible for end-to-end solutions for a diverse global customer base. Centered on data-driven technologies and innovation, these services include payments-focused consulting, loyalty and marketing programs, business Test & Learn experimentation, and data-driven information and risk management services. Within Services, the Consumer Acquisition & Engagement team is a product-centric organization focused on developing, commercializing and enhancing differentiated offerings that leverage data and marketing technology to accelerate clients’ marketing performance and business outcomes. We are looking for passionate and talented professionals, who share our vision for data-driven marketing products to join us and take a leading role in shaping the growth of our team. ________________________________________ Role: Associate Product Specialist (1-2 Years Experience) Location: Gurgaon Experience Level: 1-2 years Department: Analytics / Marketing Science / Data Science Employment Type: Full-time ________________________________________ Job Summary We are seeking a results-oriented Marketing Analytics Specialist with 2–4 years of experience in data analytics, statistical modelling, and marketing insights. The ideal candidate is confident in owning complex analyses of A/B testing and portfolio optimization and can comfortably engage with senior stakeholders. Experience in financial services, banking, or payments is strongly preferred. Exposure to GenAI in marketing analytics will be an added advantage. ________________________________________ Key Responsibilities Lead design and execution of A/B tests, campaign analytics, and test-control methodologies. Perform deep-dive analysis on customer journeys, marketing funnels, and portfolio performance. Develop predictive models to inform segmentation, personalization, and targeting strategies. Provide thought leadership in marketing measurement and performance optimization. Translate insights into business impact through crisp storytelling and stakeholder engagement. ________________________________________ Basic qualifications Undergraduate degree with 1-2 years of analytical experience in consulting, analytics, or data science with a strong focus on marketing analytics. Proficiency in tools such as SQL, Python, R, or SAS. Strong foundation in A/B testing, test-control analysis, and statistical modelling. Proven ability to communicate insights effectively with clarity and executive presence. Experience with data visualization platforms (e.g., Tableau, Power BI). Analytical, interpretive, and problem-solving skills, including the proven ability to analyze large amounts of data and synthesize key findings and recommendations Logical, structured thinking and affinity for statistical and numerical analysis Advanced Word, Excel, and PowerPoint skills Ability to manage multiple tasks and clients in a fast-paced, deadline-driven environment Ability to communicate effectively in English and the local office language (if applicable) Eligibility to work in the country where you are applying, as well as apply for travel visas as required by travel needs ________________________________________ Preferred Qualifications Background in banking, payments, or financial institutions. Experience working on digital marketing, lifecycle campaigns, or customer analytics. Exposure to or hands-on use of GenAI tools for marketing insight generation or automation. Master’s degree in Data Science, Statistics, Econometrics, Marketing, or related field is a plus. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Security represents the most critical priorities for our customers in a world awash in digital threats, regulatory scrutiny, and estate complexity. Microsoft Security aspires to make the world a safer place for all. We want to reshape security and empower every user, customer, and developer with a security cloud that protects them with end to end, simplified solutions. The Microsoft Security organization accelerates Microsoft’s mission and bold ambitions to ensure that our company and industry is securing digital technology platforms, devices, and clouds in our customers’ heterogeneous environments, as well as ensuring the security of our own internal estate. Our culture is centered on embracing a growth mindset, a theme of inspiring excellence, and encouraging teams and leaders to bring their best each day. In doing so, we create life-changing innovations that impact billions of lives around the world. We are seeking a Senior Data Scientist to join our team and work on cutting-edge solutions that safeguard Microsoft services against cyberattacks. The Senior Data Scientist will play a critical role in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity. The ideal candidate will have extensive experience in analysing large datasets, developing algorithms, and working closely with security experts to understand emerging threats and vulnerabilities. Our team values diversity in all its forms and believes in deep collaboration to harness the best of technology. We are a group of Security Engineers, Software Developers and Data Scientists with expertise in large-scale software systems, security analysis, big data, and machine learning. We delight in diving deep into the billions of events and terabytes of data generated daily by Microsoft products and services (e.g., Azure, M365) to detect and respond to suspicious activities. We ensure that critical security components are embedded throughout our infrastructure and are continuously. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day. Responsibilities Understand complex cybersecurity and business problems, translate them into well-defined data science problems, and build scalable solutions. Develop and deploy scalable, production-grade AI/ML systems for real-time threat detection and response. Drive end-to-end ML lifecycle: from data ingestion and feature engineering to model development, evaluation, and deployment. Analyse large and complex datasets generated by M365 to identify patterns and anomalies indicative of security risks. Collaborate with security experts to understand threat landscapes and incorporate domain knowledge into models. Continuously monitor and improve the performance of ML systems to adapt to evolving threats. Lead the design and implementation of data-driven security solutions and tools. Mentor and guide junior data scientists in best practices and advanced techniques. Communicate findings and insights to stakeholders, including senior leadership and technical teams. Qualifications Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurityDoctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field 5+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field Experience in programming languages such as Python, R, or Scala, with hands-on experience in data analysis, experimental design principles and visualization. Experience in translating complex data into actionable insights and recommendations that drive business impact. Excellent technical design skills and proven ability to drive large scale system designs for complex projects or products. Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). In-depth knowledge of cybersecurity principles, threats, and attack vectors. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and data processing. Strong analytical and problem-solving skills with the ability to think creatively. Excellent communication skills with the ability to explain complex concepts to non-technical stakeholders. Preferred Qualifications Experience in Experience in developing and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecuritydeveloping and deploying machine learning models for security applications. Experience in Big Data preferably in the cybersecurity. Experience with data science workloads with the Azure tech stack; Synapse, Azure ML, etc. Knowledge of anomaly detection, fraud detection, and other related areas. Familiarity with security fundamentals and attack vectors Publications or contributions to the field of data science or cybersecurity Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.