285 Xgboost Jobs - Page 4

Position Title: AI/ML Engineer Company : Cyfuture India Pvt. Ltd. Industry : IT Services and IT Consulting Location : Sector 81, NSEZ, Noida (5 Days Work From Office) Website : www.cyfuture.com About Cyfuture Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto. Position Overview We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems. Key Responsibilities Lead and mentor a high-performing AI/ML team. Design and execute AI/ML strategies aligned with business goals. Collaborate with product and engineering teams to identify impactful AI opportunities. Build, train, fine-tune, and deploy ML models in production environments. Manage operations of LLMs and other AI models using modern cloud and MLOps tools. Implement scalable and automated ML pipelines (e.g., with Kubeflow or MLRun). Handle containerization and orchestration using Docker and Kubernetes. Optimize GPU/TPU resources for training and inference tasks. Develop efficient RAG pipelines with low latency and high retrieval accuracy. Automate CI/CD workflows for continuous integration and delivery of ML systems. Key Skills & Expertise 1. Cloud Computing & Deployment Proficiency in AWS, Google Cloud, or Azure for scalable model deployment. Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML. Expertise in Docker and Kubernetes for containerized deployments Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation. 2. Machine Learning & Deep Learning Strong command of frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost. Experience with MLOps tools for integration, monitoring, and automation. Expertise in pre-trained models, transfer learning, and designing custom architectures. 3. Programming & Software Engineering Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development. Backend/API development with FastAPI, Flask, or Django. Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery). Familiarity with CI/CD pipelines (GitHub Actions, Jenkins). 4. Scalable AI Systems Proven ability to build AI-driven applications at scale. Handle large datasets, high-throughput requests, and real-time inference. Knowledge of distributed computing: Apache Spark, Dask, Ray. 5. Model Monitoring & Optimization Hands-on with model compression, quantization, and pruning. A/B testing and performance tracking in production. Knowledge of model retraining pipelines for continuous learning. 6. Resource Optimization Efficient use of compute resources: GPUs, TPUs, CPUs. Experience with serverless architectures to reduce cost. Auto-scaling and load balancing for high-traffic systems. 7. Problem-Solving & Collaboration Translate complex ML models into user-friendly applications. Work effectively with data scientists, engineers, and product teams. Write clear technical documentation and architecture reports. Show more Show less

We are seeking a talented and motivated Data Scientist with 1-3 years of experience to join our Data Science team. If you have a strong passion for data science, expertise in machine learning, and experience working with large-scale datasets, we want to hear from you. As a Data Scientist at RevX, you will play a crucial role in developing and implementing machine learning models to drive business impact. You will work closely with teams across data science, engineering, product, and campaign management to build predictive models, optimize algorithms, and deliver actionable insights. Your work will directly influence business strategy, product development, and campaign optimization. Major Responsibilities: Develop and implement machine learning models, particularly neural networks, decision trees, random forests, and XGBoost, to solve complex business problems. Work on deep learning models and other advanced techniques to enhance predictive accuracy and model performance. Analyze and interpret large, complex datasets using Python, SQL, and big data technologies to derive meaningful insights. Collaborate with cross-functional teams to design, build, and deploy end-to-end data science solutions, including data pipelines and model deployment frameworks. Utilize advanced statistical techniques and machine learning methodologies to optimize business strategies and outcomes. Evaluate and improve model performance, calibration, and deployment strategies for real-time applications. Perform clustering, segmentation, and other unsupervised learning techniques to discover patterns in large datasets. Conduct A/B testing and other experimental designs to validate model performance and business strategies. Create and maintain data visualizations and dashboards using tools such as matplotlib, seaborn, Grafana, and Looker to communicate findings. Provide technical expertise in handling big data, data warehousing, and cloud-based platforms like Google Cloud Platform (GCP). Required Experience/Skills: Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. 1-3 years of experience in data science or machine learning roles. Strong proficiency in Python for machine learning, data analysis, and deep learning applications. Experience in developing, deploying, and monitoring machine learning models, particularly neural networks, and other advanced algorithms. Expertise in handling big data technologies, with experience in tools such as BigQuery and cloud platforms (GCP preferred). Advanced SQL skills for data querying and manipulation from large datasets. Experience in data visualization tools like matplotlib, seaborn, Grafana, and Looker. Strong understanding of A/B testing, statistical tests, experimental design, and methodologies. Experience in clustering, segmentation, and other unsupervised learning techniques. Strong problem-solving skills and the ability to work with complex datasets and machine learning pipelines. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Preferred Skills: Experience with deep learning frameworks such as TensorFlow or PyTorch. Familiarity with data warehousing concepts and big data tools. Knowledge of MLOps practices, including model deployment, monitoring, and management. Experience with business intelligence tools and creating data-driven dashboards. Understanding of reinforcement learning, natural language processing (NLP), or other advanced AI techniques. Education: Bachelor of Engineering or similar degree from any reputed University.

Research and Problem-Solving: Identify and frame business problems, conduct exploratory data analysis, and propose innovative data science solutions tailored to business needs. Leadership & Communication: Serve as a technical referent for the research team, driving high-impact, high-visibility initiatives. Effectively communicate complex scientific concepts to senior stakeholders, ensuring insights are actionable for both technical and non-technical audiences. Mentor and develop scientists within the team, fostering growth and technical excellence. Algorithm Development: Design, optimize, and implement advanced machine learning algorithms, including neural networks, ensemble models (XGBoost, random forests), and clustering techniques. End-to-End Project Ownership: Lead the development, deployment, and monitoring of machine learning models and data pipelines for large-scale applications. Model Optimization and Scalability: Focus on optimizing algorithms for performance and scalability, ensuring robust, well-calibrated models suitable for real-time environments. A/B Testing and Validation: Design and execute experiments, including A/B testing, to validate model effectiveness and business impat. Big Data Handling: Leverage tools like BigQuery, advanced SQL, and cloud platforms (e.g., GCP) to process and analyze large datasets. Collaboration and Mentorship: Work closely with engineering, product, and campaign management teams, while mentoring junior data scientists in best practices and advanced techniques. Data Visualization: Create impactful visualizations using tools like matplotlib, seaborn, Looker, and Grafana to communicate insights effectively to stakeholders. Required Experience/Skills 5–8 years of hands-on experience in data science or machine learning roles. 2+ years leading data science projects in AdTech Strong hands-on skills in Advanced Statistics, Machine Learning, and Deep Learning. Demonstrated ability to implement and optimize neural networks and other advanced ML models. Proficiency in Python for developing machine learning models, with a strong grasp of TensorFlow or PyTorch. Expertise handling large datasets using advanced SQL and big data tools like BigQuery In-depth knowledge of MLOps pipelines, from data preprocessing to deployment and monitoring. Strong background in A/B testing, statistical analysis, and experimental design. Proven capability in clustering, segmentation, and unsupervised learning methods. Strong problem-solving and analytical skills with a focus on delivering business value. Education: A Master’s in Data Science, Computer Science, Mathematics, Statistics, or a related field is preferred. A Bachelor's degree with exceptional experience will also be considered.

Quantitative Analyst: Hillroute Capital About Hillroute: Hillroute Capital is a regulated quantitative hedge fund specializing in global digital asset trading. We leverage sophisticated quantitative methodologies and advanced technology to achieve exceptional risk-adjusted returns. Our transparent approach and diverse, experienced team allow us to excel in the rapidly evolving digital asset market. About the Role: We are seeking a highly skilled Quantitative Analyst to develop, test, and refine systematic trading models across global digital asset markets. This role offers flexibility in approach—candidates with expertise in systematic strategies, options trading, statistical arbitrage, backtesting, or machine learning are equally encouraged to apply. This role will be in the US shift. Key Responsibilities: Strategy Development & Backtesting: Design and rigorously backtest quantitative trading models, ensuring predictive reliability and strong risk management. Quantitative & Statistical Analysis: Apply advanced statistical modeling, econometric analysis, or financial mathematics to extract market insights. Risk Management: Contribute actively to robust risk management frameworks, identifying potential risks and implementing mitigation strategies. Innovation: Regularly generate and test new ideas and strategies, pushing boundaries to enhance fund performance. Preferred Qualifications: 3–5 years experience in quantitative analysis, trading, or research roles within finance. 1-3 years experience in running quantitative machine learning models. Advanced degree in quantitative disciplines (Mathematics, Physics, Statistics, Computer Science, Engineering). Strong Python programming skills (NumPy, Pandas), and familiarity with backtesting frameworks (Backtrader, QuantConnect). Solid knowledge in options pricing, volatility modeling, statistical arbitrage, or systematic strategies. Familiarity with financial data platforms (Bloomberg, Refinitiv, Quandl). Exposure to cloud computing environments (AWS, GCP, Azure). Experience or interest in applying machine learning techniques (XGBoost, TensorFlow, PyTorch) is a plus—but not mandatory. Participation in Kaggle or similar platforms is beneficial but not required. Key Performance Indicators (KPIs): Model profitability and risk-adjusted returns. Backtest reliability and accuracy. Effectiveness in risk management. Contribution to innovation and research quality. What We Offer: Competitive compensation and performance-based incentives. The opportunity to pioneer quantitative strategies in the dynamic digital asset industry. A collaborative, inclusive, and flexible working environment. Professional growth in an innovative, fast-paced hedge fund setting. If you're passionate about quantitative finance and thrive in a dynamic, data-driven environment, we invite you to join our team. Apply directly via LinkedIn: Hillroute Capital Show more Show less

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Manager Job Description & Summary A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Creating business intelligence from data requires an understanding of the business, the data, and the technology used to store and analyse that data. Using our Rapid Business Intelligence Solutions, data visualisation and integrated reporting dashboards, we can deliver agile, highly interactive reporting and analytics that help our clients to more effectively run their business and understand what business questions can be answered and how to unlock the answers. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. " Job Description & Summary : Manager Advanced Analytics & ML – Financial Services Responsibilities This is for an opening at the Manager level in the Data and Analytics division at PwC India. The role will be centered around Financial services domain. A successful candidate is expected to work pro-actively and effectively on multiple client engagements and take ownership of the entire project delivery. This includes having project management skills, technical and/or functional expertise, and commitment to comply with the PwC delivery quality expectation. Further, this role requires a candidate with strong interpersonal skills, who not only enjoys the challenge of working with other teams but externally with a variety of clients as well. Strong personal and professional presence and self-confidence, capable of working effectively with senior team as well as all other levels. The candidate will be required to showcase excellent communication skills and will have demonstrated consistently the skill and capability in delivering impactful and insightful projects in the past. He/she will also be required to participate in client meetings, understand the business needs and then design end to end machine learning and analytics solutions to fulfill those business needs. They will also be expected to contribute to practice or Firm development. This may be adjudged in various ways such as serving as a mentor to other team members, by leading training/development initiatives, contributing to thought leadership papers, and developing reusable assets. Detailed role and responsibilities are provided below: Roles and Responsibilities: Develop, Review and implement Solutions applying advanced analytics techniques including but not restricted to Machine Learning, Deep Learning, AI, NLP and Visualization Troubleshoot, isolate and remediate model errors. Work on and manage large to mid-size projects, and ensure smooth service delivery on assigned products, engagements and/or geographies. Work with project leaders to analyse resource needs and gaps and devise alternative ways forward. Provide expert reviews for all projects within the assigned subject Ability to lead business development initiatives including responding to RFPs, preparation and delivery of client presentations with the objective of sales and business development. Ability to manage cross functional teams and mentor junior team members Understanding of statistical methods to enable appropriate interpretation of results Experience analyzing programs through the lens of client requirements and design optimal solutions for fulfilling those requirements. Conceptual thinking and ability to find innovative ways to solve analytical problems Should have worked on multiple analytics consulting and implementation projects Skills & Qualifications Required: Minimum 8-10 years of experience in advanced analytics and machine learning space with at least 4-6 years of experience in financial services. Advanced understanding and hands-on experience in SQL and at least one of R or Python. Basic exposure to other statistical packages such as R, Python and SAS. Deep understanding of predictive algorithms such as logistic regression, linear regression, decision trees, random forest, xgboost, SVM etc. and clustering algorithms such as k-means, k nearest neighbour, hierarchical etc. Hands on experience in NLP and deep understanding of text analytics algorithms and modelling workflow Good knowledge of neural networks, deep learning, RNN, CNN, LSTM etc, Working knowledge of big data environment setups such as Spark, PySpark, Hive, Hadoop etc. Advanced understanding of Cloud (AWS, Azure, etc.) and good exposure to Azure/AWS machine learning workbench and MLOps workflow. Excellent verbal and written communication skills. Experienced in creating power point presentations, dashboards, solving complicated client problems and communicating the precise insights. Strong organizational skills & the ability to prioritize and work on projects with great efficiency & attention to the details. Minimum qualification – B.E; MBA is preferred (with at least 5 years of exp. post MBA) Mandatory Skill Sets Advanced Analytics & ML Preferred Skill Sets Advanced Analytics & ML Years Of Experience Required 9+ Education Qualification BTech/MBA/MCA Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor of Engineering, Master of Business Administration Degrees/Field Of Study Preferred Certifications (if blank, certifications not specified) Required Skills Advanced Analytics Optional Skills Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date Show more Show less

By clicking the “Apply” button, 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’s Privacy Notice and 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. About The Role We are seeking an innovative and skilled Principal AI/ML Engineer with a strong focus on designing and deploying scalable machine learning solutions. This role requires a strategic thinker who can architect production-ready solutions, collaborate closely with cross-functional teams, and ensure adherence to Takeda’s technical standards through participation in the Architecture Council. The ideal candidate has extensive experience in operationalizing ML models, MLOps workflows, and building systems aligned with healthcare standards. By leveraging cutting-edge machine learning and engineering principles, this role supports Takeda’s global mission of delivering transformative therapies to patients worldwide. How You Will Contribute Architect scalable and secure machine learning systems that integrate with Takeda’s enterprise platforms, including R&D, manufacturing, and clinical trial operations. Design and implement pipelines for model deployment, monitoring, and retraining using advanced MLOps tools such as MLflow, Airflow, and Databricks. Operationalize AI/ML models for production environments, ensuring efficient CI/CD workflows and reproducibility. Collaborate with Takeda’s Architecture Council to propose and refine AI/ML system designs, balancing technical excellence with strategic alignment. Implement monitoring systems to track model performance (accuracy, latency, drift) in a production setting, using tools such as Prometheus or Grafana. Ensure compliance with industry regulations (e.g., GxP, GDPR) and Takeda’s ethical AI standards in system deployment. Identify use cases where machine learning can deliver business value, and propose enterprise-level solutions aligned to strategic goals. Work with Databricks tools and platforms for model management and data workflows, optimizing solutions for scalability. Manage and document the lifecycle of deployed ML systems, including versioning, updates, and data flow architecture. Drive adoption of standardized architecture and MLOps frameworks across disparate teams within Takeda. Skills And Qualifications Education Bachelors or Master’s or Ph.D. in Computer Science, Software Engineering, Data Science, or related field. Experience At least 6-8 years of experience in machine learning system architecture, deployment, and MLOps, with a significant focus on operationalizing ML at scale. Proven track record in designing and advocating ML/AI solutions within enterprise architecture frameworks and council-level decision-making. Technical Skills Proficiency in deploying and managing machine learning pipelines using MLOps tools like MLflow, Airflow, Databricks, or Clear ML. Strong programming skills in Python and experience with machine learning libraries such as Scikit-learn, XGBoost, LightGBM, and TensorFlow. Deep understanding of CI/CD pipelines and tools (e.g., Jenkins, GitHub Actions) for automated model deployment. Familiarity with Databricks tools and services for scalable data workflows and model management. Expertise in building robust observability and monitoring systems to track ML systems in production. Hands-on experience with classical machine learning techniques, such as random forests, decision trees, SVMs, and clustering methods. Knowledge of infrastructure-as-code tools like Terraform or CloudFormation to enable automated deployments. Experience in handling regulatory considerations and compliance in healthcare AI/ML implementations (e.g., GxP, GDPR). Soft Skills Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills for influencing technical and non-technical stakeholders. Leadership ability to mentor teams and drive architecture-standardization initiatives. Ability to manage projects independently and advocate for AI/ML adoption across Takeda. Preferred Qualifications Real-world experience operationalizing machine learning for pharmaceutical domains, including drug discovery, patient stratification, and manufacturing process optimization. Familiarity with ethical AI principles and frameworks, aligned with FAIR data standards in healthcare. Publications or contributions to AI research or MLOps tooling communities. 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 Health & Wellness programs including annual health screening, weekly health sessions for employees. Employee Assistance Program 5 days of leave every year for Voluntary Service in additional to Humanitarian Leaves Broad Variety of learning platforms Diversity, Equity, and Inclusion Programs No Meeting Days 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. Locations: IND - Bengaluru Worker Type: Employee Worker Sub-Type: Regular Time Type: Full time Show more Show less

PwC is one of the most prestigious professional services firm in the world, serving as the auditor to nearly half of the world’s largest banks. PwC US Risk and Regulatory (R&R) comprises of a highly experienced team of risk management specialists supporting global financial institutions in their risk management initiatives. R&R has significant exposure to, and driver of, industry leading practices and has deep knowledge of regulatory expectations. R&R professional’s experience covers all financial model types, including those used to manage credit risk, market risk, operational risk and compliance risk—as well as those used for financial reporting, valuations and economic capital estimation. Risk Analytics Center of Excellence (CoE) is the India extension of R&R practice and provides key risk analytics services to global banks, investment firms, and asset management entities. It comprises of risk analytics professionals with stellar quantitative pedigree from premier institutions, industry certifications in CFA, FRM, PRM etc. and proven professional credentials in risk modeling and analytics at reputed financial institutions and consulting firms. As an integral part of PwC US R&R, Risk Analytics CoE drives risk analytics engagements, opportunity pursuits and cutting-edge innovation using data science, Artificial Intelligence, Machine Learning and Deep Learning. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred Show more Show less

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred Show more Show less

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Driven by curiosity, you are a reliable, contributing member of a team. In our fast-paced environment, you are expected to adapt to working with a variety of clients and team members, each presenting varying challenges and scope. Every experience is an opportunity to learn and grow. You are expected to take ownership and consistently deliver quality work that drives value for our clients and success as a team. As you navigate through the Firm, you build a brand for yourself, opening doors to more opportunities. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Apply a learning mindset and take ownership for your own development. Appreciate diverse perspectives, needs, and feelings of others. Adopt habits to sustain high performance and develop your potential. Actively listen, ask questions to check understanding, and clearly express ideas. Seek, reflect, act on, and give feedback. Gather information from a range of sources to analyse facts and discern patterns. Commit to understanding how the business works and building commercial awareness. Learn and apply professional and technical standards (e.g. refer to specific PwC tax and audit guidance), uphold the Firm's code of conduct and independence requirements. AI/ML & Credit Risk Analytics Professional – Job Specification Candidate would be responsible for developing, validating, auditing, and maintaining AI/ML-powered credit risk models. Candidates would be expected to support financial institutions in meeting jurisdictional regulatory requirements and their broader risk management initiatives. Multiple positions required; Experience level: 2–6 years of relevant experience Location: Bangalore Role Overview We are looking for high-caliber professionals with strong foundations in credit risk modeling and hands-on experience in AI/ML techniques. The ideal candidate will contribute to the development and validation of regulatory and strategic risk models, while also applying machine learning and generative AI techniques to enhance model accuracy, efficiency, and interpretability. Key Responsibilities Develop, validate, and document credit risk models (PD, LGD, EAD) for retail and wholesale portfolios across regulatory (CECL, IFRS 9, Basel) and business-use contexts. Apply AI/ML algorithms (e.g., LightGBM, XGBoost, Random Forest, Neural Networks) to improve prediction power and model performance beyond traditional approaches. Implement Generative AI and LLM-based applications using RAG pipelines, document intelligence, and model documentation automation. Experience with agentic frameworks like Autogen, LangChain, or similar would be helpful. Experience of development and deployment of models in cloud-based platforms such as Azure, AWS, GCP etc. Design explainable AI solutions by incorporating techniques like SHAP, LIME, and feature attribution methods to enhance transparency in high-stakes modeling environments. Partner with cross-functional teams, including business stakeholders, technology teams, and model governance, to ensure model alignment with business objectives and regulatory expectations. Contribute to innovation initiatives and support proposal development, thought leadership, and solution architecture in the AI/ML space. Required Skills & Experience 2–6 years of total experience, with minimum 2 years in AI/ML or GenAI model development or validation. Strong understanding of credit risk modeling frameworks, scorecard development, and risk metrics (e.g., RWA, Expected Loss, Economic Capital). Proficient in Python and SQL, with hands-on experience using ML libraries such as scikit-learn, Tensorflow, Pytorch and transformer-based LLM packages Familiarity with regulatory standards such as CECL, IFRS 9, CCAR/DFAST, Basel II/III, SR 11-7, and model governance best practices. Exposure to cloud environments (Azure preferred), version control (Git), and workflow automation tools. Experience with credit bureau data, vendor models (e.g., FICO, Moody’s, S&P), and financial benchmarking is a plus. Ability to clearly communicate complex technical content to non-technical stakeholders through reports, dashboards, and presentations. Education & Certifications Master’s degree or higher in Statistics, Mathematics, Economics, Data Science, Engineering, or Finance. Professional certifications such as FRM, CFA, CQF, or in product management equivalent are preferred. Contributions to opensource AI / ML projects and competitions is preferred Show more Show less

We are seeking a motivated and analytical AI Intern (Developer) to join our team for a 6-month internship. This is a unique opportunity to gain hands-on experience working on real-world AI solutions in fintech and insurance — two of the most data-rich and fast-evolving sectors. The ideal candidate should have strong expertise in Postgres database/Oracle, Express.js, React.js, and Node.js , with a focus on both front-end and back-end development. Responsibilities: Assist in developing machine learning models for use cases. Perform data cleaning, analysis, and feature engineering. Work with structured and unstructured financial/insurance, etc. data Collaborate with data engineers and domain experts to deploy AI models. Research industry trends in AI for fintech and insurance tech Document experiments, model results, and insights Conduct unit and integration testing to maintain code quality. Collaborate with cross-functional teams to deliver seamless user experiences. Troubleshoot and resolve technical issues. Manage and guide the development team effectively. Requirements: Strong Python programming skills Familiarity with ML libraries: scikit-learn, XGBoost, TensorFlow/PyTorch Understanding of supervised and unsupervised learning techniques Good with data wrangling using Pandas, NumPy, SQL Experience with NLP or OCR tools Strong analytical and problem-solving skills Strong proficiency in MERN Stack (MongoDB, Express.js, React.js, Node.js) . Experience in REST API development and integration . Ability to manage time efficiently and meet deadlines. Team player with excellent communication skills . Delivery-focused mindset with the ability to work under minimal supervision. Company: ATS Services is a leading service provider in the Indian BFSI Industry. We inculcate a work environment that promotes diversity, embraces change and provides leadership opportunities. We provide consulting, services and IT solutions to our customers in the areas of credit & risk, risk analytics, development of scorecards and segmentation models, collections for retail and B2B Customers, Insurance retention and a variety of IT solutions in the areas of credit MIS, business intelligence and business process consulting and automation. Qualification: Tech Computer/IT Applications Experience – Fresher Proficiency in Languages: English and Hindi Duration 6 months Benefits: Stipend +PF+ Insurance. 5 Days working Day Shift Location – Faridabad work from office www.servicesats.com If you are interested in above position, you can apply and appear for the interview, or you may get in touch with us as undersigned, hiring@servicesats.com

Responsibilities: Collaborate with cross-functional teams on project requirements & deliverables. Design, develop, test & maintain Python apps using Django/Flask & AWS/Azure Cloud.

About ISOCRATES Since 2015, iSOCRATES advises on, builds and manages mission-critical Marketing, Advertising and Data technologies, platforms, and processes as the Global Leader in MADTECH Resource Planning and Execution(TM). iSOCRATES delivers globally proven, reliable, and affordable Strategy and Operations Consulting and Managed Services for marketers, agencies, publishers, and the data/tech providers that enable them. iSOCRATES is staffed 24/7/365 with its proven specialists who save partners money, and time and achieve transparent, accountable, performance while delivering extraordinary value. Savings stem from a low-cost, focused global delivery model at scale that benefits from continuous re-investment in technology and specialized training. About MADTECH.AI MADTECH.AI is the Unified Marketing, Advertising, and Data Decision Intelligence Platform purpose-built to deliver speed to value for marketers. At MADTECH.AI, we make real-time AI-driven insights accessible to everyone. Whether you’re a global or emerging brand, agency, publisher, or data/tech provider, we give you a single source of truth - so you can capture sharper insights that drive better marketing decisions faster and more affordable than ever before. MADTECH.AI unifies and transforms MADTECH data and centralizes decision intelligence in a single, affordable platform. Leave data wrangling, data model building, proactive problem solving, and data visualization to MADTECH.AI. Job Description We are seeking a highly skilled, results-oriented Product Manager - AI & BI to lead the growth and development of iSOCRATES' MADTECH.AI™ platform. As a core member of the product team, you will play an instrumental role in shaping the future of our AI-powered Marketing, Advertising, and Data Decision Intelligence solutions. Your focus will be on driving innovation in AI and BI capabilities, ensuring that our product meets the evolving needs of our B2B customers and enhances their marketing and data analytics capabilities. Key Responsibilities Product Strategy & Roadmap Development: Lead the creation and execution of the MADTECH.AI™ product roadmap, with a focus on incorporating AI and BI technologies to deliver value for B2B customers. Collaborate with internal stakeholders to define product features, prioritize enhancements, and ensure alignment with iSOCRATES’ long-term business objectives. AI & BI Product Development: Spearhead the design and development of innovative AI and BI features to enhance the MADTECH.AI™ platform’s scalability, functionality, and user experience. Leverage cutting-edge technologies such as machine learning, predictive analytics, natural language processing (NLP), data visualization, reinforcement learning, and other advanced AI techniques to deliver powerful marketing, advertising, and data decision intelligence solutions. Cross-Functional Collaboration: Collaborate with cross-functional teams, including engineering, design, marketing, sales, and customer success, to ensure seamless product development and delivery. Facilitate communication between technical and business teams to ensure product features align with customer needs and market trends. Customer & Market Insights: Engage with customers and other stakeholders to gather feedback, identify pain points, and stay on top of market trends. Use this data to shape product development and enhance MADTECH.AI™ capabilities, ensuring they are well-positioned in the evolving market landscape. Product Lifecycle Management: Oversee the complete product lifecycle from ideation through launch and beyond. Manage ongoing iterations of the product based on customer feedback and performance metrics to ensure that MADTECH.AI™ remains competitive and meets user expectations. Data-Driven Decision Making: Use customer analytics, usage patterns, and performance data to inform key product decisions. Define success metrics, monitor product performance, and make adjustments as needed to drive product success. AI/BI Thought Leadership: Stay current on the latest trends in AI, BI, MarTech, and AdTech. Act as a thought leader both internally and externally to position iSOCRATES as an innovator in the MADTECH.AI space. Promote best practices and contribute to the company’s overall strategy for AI and BI product development. Qualifications & Skills Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Business, or a related field. At least 12 years of experience in product management, with a minimum of 7 years focused on B2B SaaS solutions and strong expertise in AI and BI technologies. Prior experience in marketing, advertising, or data analytics platforms is highly preferred. AI & BI Expertise: Deep understanding of Artificial Intelligence, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Data Visualization, Business Intelligence tools (e.g., Tableau, Power BI, Qlik), and their application in SaaS products, especially within the context of MarTech, AdTech, or DataTech. AI Tools and Technologies : Hands-on experience with AI and BI tools such as: Data Science Libraries: TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, Hugging Face Transformers, CatBoost, H2O.ai BI Platforms: Tableau, Power BI, Qlik, Looker, Domo, Sisense, MicroStrategy Machine Learning Tools: Azure ML, Google AI Platform, AWS Sagemaker, Databricks, H2O.ai, Vertex AI Data Analytics Tools: Apache Hadoop, Apache Spark, Apache Flink, SQL-based tools, dbt, Snowflake Data Visualization Tools: D3.js, Plotly, Matplotlib, Seaborn, Chart.js, Superset Cloud-Based AI Services: Google AI, AWS AI/ML services, IBM Watson, Microsoft Azure Cognitive Services, Oracle Cloud AI Emerging Tools: AutoML platforms, MLOps tools, Explainable AI (XAI) tools Product Development: Proven experience in leading AI/BI-driven product development within SaaS platforms, including managing the full product lifecycle, from ideation to launch and post-launch iterations. Agile Methodology: Experience working in Agile product development environments, with the ability to prioritize and manage multiple initiatives and product features simultaneously. Analytical & Data-Driven: Strong analytical skills with a focus on leveraging data, performance metrics, and customer feedback to inform product decisions. Ability to translate complex data into actionable insights. Customer-Centric: Experience in working directly with customers to understand their needs, pain points, and feedback. A customer-first mindset with a focus on building products that provide measurable value. Excellent Communication Skills: Exceptional communication, presentation, and interpersonal skills, with the ability to engage and influence both technical teams and business stakeholders across different geographies. Industry Knowledge: Familiarity with MADTECH.AI platforms and technologies. Understanding of customer journey analytics, predictive analytics, and decision intelligence platforms like MADTECH.AI™ is a plus. Cloud & SaaS Architecture: Familiarity with cloud-based solutions and large-scale SaaS architecture. Understanding of how AI and BI features integrate with cloud infrastructure is beneficial. Experience with AI-powered decision intelligence platforms like MADTECH.AI™ or similar MarTech, AdTech, or DataTech tools. In-depth knowledge of cloud technologies, including AWS, Azure, or Google Cloud, and their integration with SaaS platforms. Exposure to customer journey analytics, predictive analytics, and other advanced AI/BI tools. Willingness to work from Mysore/Bangalore or travel to Mysore as per business requirement. Show more Show less

Quantitative Analyst: Hillroute Capital About Hillroute: Hillroute Capital is a regulated quantitative hedge fund specializing in global digital asset trading. We leverage sophisticated quantitative methodologies and advanced technology to achieve exceptional risk-adjusted returns. Our transparent approach and diverse, experienced team allow us to excel in the rapidly evolving digital asset market. About the Role: We are seeking a highly skilled Quantitative Analyst to develop, test, and refine systematic trading models across global digital asset markets. This role offers flexibility in approach—candidates with expertise in systematic strategies, options trading, statistical arbitrage, backtesting, or machine learning are equally encouraged to apply. Key Responsibilities: Strategy Development & Backtesting: Design and rigorously backtest quantitative trading models, ensuring predictive reliability and strong risk management. Quantitative & Statistical Analysis: Apply advanced statistical modeling, econometric analysis, or financial mathematics to extract market insights. Risk Management: Contribute actively to robust risk management frameworks, identifying potential risks and implementing mitigation strategies. Innovation: Regularly generate and test new ideas and strategies, pushing boundaries to enhance fund performance. Preferred Qualifications: 3–5 years experience in quantitative analysis, trading, or research roles within finance. 1-3 years experience in running quantitative machine learning models. Advanced degree in quantitative disciplines (Mathematics, Physics, Statistics, Computer Science, Engineering). Strong Python programming skills (NumPy, Pandas), and familiarity with backtesting frameworks (Backtrader, QuantConnect). Solid knowledge in options pricing, volatility modeling, statistical arbitrage, or systematic strategies. Familiarity with financial data platforms (Bloomberg, Refinitiv, Quandl). Exposure to cloud computing environments (AWS, GCP, Azure). Experience or interest in applying machine learning techniques (XGBoost, TensorFlow, PyTorch) is a plus—but not mandatory. Participation in Kaggle or similar platforms is beneficial but not required. Key Performance Indicators (KPIs): Model profitability and risk-adjusted returns. Backtest reliability and accuracy. Effectiveness in risk management. Contribution to innovation and research quality. What We Offer: Competitive compensation and performance-based incentives. The opportunity to pioneer quantitative strategies in the dynamic digital asset industry. A collaborative, inclusive, and flexible working environment. Professional growth in an innovative, fast-paced hedge fund setting. If you're passionate about quantitative finance and thrive in a dynamic, data-driven environment, we invite you to join our team. Apply directly via LinkedIn: Hillroute Capital Show more Show less

Dear Associate Greetings from TATA Consultancy Services!! Thank you for expressing your interest in exploring a career possibility with the TCS Family. We have a job opportunity for at Tata Consultancy Services at 14th June 2025. Hiring For : AWS Data Scientist Mandatory Skills: Python AI ML, MlOPs, Spark, Hadoop,PyTorch, TensorFlow,Matplotlib, Seaborn, Tableau, Power BI,scikit-learn, TensorFlow, XGBoost,AWS,Azure , AWS, Databricks,Pyspark, Python,SQL, Snowflake Walk in Location: Pune Experience : 5-15 years Mode of interview: in-person walk in drive Date of interview: 14 June 2025 Venue : Zone 3 Auditorium, Tata Consultancy Services, Sahyadri Park, Rajiv Gandhi Infotech Park, Hinjewadi Phase 3, Pune – 411057 If you are interested in this exciting opportunity, Please share your updated resume on jeena.james1@tcs.com along with the additional information mentioned below: Name: Preferred Location: Contact No: Email id: Highest Qualification: Current Organization Total Experience: Relevant Experience in Data Scientist: Current CTC: Expected CTC: Notice Period: Gap Duration: Gap Details: Attended interview with TCS in past(details): Please share your I begin portal EP id if already registered: Willing to attend walk in on 14th June: (Yes/No) Note: only Eligible candidates with Relevant experience will be contacted further Thanks & Regards, Jeena James, Website: http://www.tcs.com Email: jeena.james1@tcs.com Human Resource - Talent Acquisition Group, Tata Consultancy Services Show more Show less

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems. Years of Experience: Candidates with 12+ years of hands on experience Position: Senior Manager Required Skills: Successful candidates will have demonstrated the following skills and characteristics: Must Have Deep expertise in AI/ML solution design, including supervised and unsupervised learning, deep learning, NLP, and optimization. Strong hands-on experience with ML/DL frameworks like TensorFlow, PyTorch, scikit-learn, H2O, and XGBoost. Solid programming skills in Python, PySpark, and SQL, with a strong foundation in software engineering principles. Proven track record of building end-to-end AI pipelines, including data ingestion, model training, testing, and production deployment. Experience with MLOps tools such as MLflow, Airflow, DVC, and Kubeflow for model tracking, versioning, and monitoring. Understanding of big data technologies like Apache Spark, Hive, and Delta Lake for scalable model development. Expertise in AI solution deployment across cloud platforms like GCP, AWS, and Azure using services like Vertex AI, SageMaker, and Azure ML. Experience in REST API development, NoSQL database design, and RDBMS design and optimizations. Familiarity with API-based AI integration and containerization technologies like Docker and Kubernetes. Proficiency in data storytelling and visualization tools such as Tableau, Power BI, Looker, and Streamlit. Programming skills in Python and either Scala or R, with experience using Flask and FastAPI. Experience with software engineering practices, including use of GitHub, CI/CD, code testing, and analysis. Proficient in using AI/ML frameworks such as TensorFlow, PyTorch, and SciKit-Learn. Skilled in using Apache Spark, including PySpark and Databricks, for big data processing. Strong understanding of foundational data science concepts, including statistics, linear algebra, and machine learning principles. Knowledgeable in integrating DevOps, MLOps, and DataOps practices to enhance operational efficiency and model deployment. Experience with cloud infrastructure services like Azure and GCP. Proficiency in containerization technologies such as Docker and Kubernetes. Familiarity with observability and monitoring tools like Prometheus and the ELK stack, adhering to SRE principles and techniques. Cloud or Data Engineering certifications or specialization certifications (e.g. Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate – Exam AI-102, AWS Certified Machine Learning – Specialty (MLS-C01), Databricks Certified Machine Learning) Nice To Have Experience implementing generative AI, LLMs, or advanced NLP use cases Exposure to real-time AI systems, edge deployment, or federated learning Strong executive presence and experience communicating with senior leadership or CXO-level clients Roles And Responsibilities Lead and oversee complex AI/ML programs, ensuring alignment with business strategy and delivering measurable outcomes. Serve as a strategic advisor to clients on AI adoption, architecture decisions, and responsible AI practices. Design and review scalable AI architectures, ensuring performance, security, and compliance. Supervise the development of machine learning pipelines, enabling model training, retraining, monitoring, and automation. Present technical solutions and business value to executive stakeholders through impactful storytelling and data visualization. Build, mentor, and lead high-performing teams of data scientists, ML engineers, and analysts. Drive innovation and capability development in areas such as generative AI, optimization, and real-time analytics. Contribute to business development efforts, including proposal creation, thought leadership, and client engagements. Partner effectively with cross-functional teams to develop, operationalize, integrate, and scale new algorithmic products. Develop code, CI/CD, and MLOps pipelines, including automated tests, and deploy models to cloud compute endpoints. Manage cloud resources and build accelerators to enable other engineers, with experience in working across two hyperscale clouds. Demonstrate effective communication skills, coaching and leading junior engineers, with a successful track record of building production-grade AI products for large organizations. Professional And Educational Background BE / B.Tech / MCA / M.Sc / M.E / M.Tech /Master’s Degree /MBA from reputed institute Show more Show less

We are seeking a candidate with strong working experience in both Data Scientist . The ideal candidate must have utilized Azure services related to data, data engineering, and machine learning. PAN India. Machine Learning 7+ years of relevant experience Experience in handling ETRM projects. Good understanding of Power Trading concepts Must have good experience in implementing machine learning models such as Prophet, ARIMA, SARIMA, XGBoost, ElasticNet, Ridge, Lasso, Random Forest, and Linear Regression on time-series data. Proficient in using Python ML packages such as scikit-learn, sktime, and darts. Must have strong expertise in key techniques for time series feature engineering, including lag features, rolling window statistics, Fourier transforms, and handling seasonality. Proven ability to tune the performance of existing deployed forecasting models. Must have experience with Azure Machine Learning Python SDK v1/v2 to: Manage data, models, and environments Build/debug AML pipelines to stitch together multiple tasks (feature engineering, training, registering models, etc.) and production workflows using Azure ML pipelines Schedule Azure ML jobs Deploy registered models to create endpoints. Good to have experience with K-Means clustering.

Who we are : Money. A subject that’s always on our mind. We go through a rollercoaster of emotions when it comes to money. That’s why at Jupiter, our mission is to enable people to improve their relationship with money. We are a financial services platform that leverages technology to offer our customers seamless and user-friendly products related to banking, loans, and investments. So whether it’s a savings account, credit cards, investment and payments, it's all on Jupiter. We also help users cut through the banking jargons, offer smart insights based on spending and provide users with a range of new age features to enable and make sense of their finances. Our journey so far: Jupiter was founded in 2019 by Jitendra Gupta. Best known as Citrus Pay’s founder, Jiten found himself wondering why personal finance experiences were not customer-centric when everything else like food ordering and entertainment were. That’s how our journey began in 2019, with a simple, powerful idea : to create a modern, customer-centric experience that empowers individuals when it comes to their money. From our humble beginnings, we've strived relentlessly to make managing money easier. In 2021 when we launched we had a waitlist with over 100,000 people eager to experience the world of Jupiter - and within 10 months we crossed 1 million users. Today, we have 2.7 million + happy users on Jupiter. Our Insights feature today tells how much and where you’ve been spending automatically, even on your other savings accounts! Our Edge CSB Bank RuPay credit card is getting a lot of love for it’s head-turning transparent design, not to mention it being a rewarding experience. Our No-Penalty SIP and Daily SIP at Rs 10/- has helped scale our investments business and we have over 100,000 users investing on our platform to fulfill their money aspirations. We've embraced cutting-edge technology, harnessed the power of data analytics, and assembled a diverse team of creative thinkers and industry experts who share our vision for a more accessible, transparent, and inclusive financial ecosystem. We’re now looking for like-minded folks to join the crew. Who we're looking for : You are passionate about using data to solve complex problems and enjoy building models that drive real-time decisions. You think like a data scientist and a risk strategist—comfortable testing hypotheses, uncovering patterns, and translating insights into actionable strategies. You enjoy working with large, messy datasets and can extract meaning through strong visualization and storytelling skills. You are excited by the opportunity to help shape the risk framework of a digital-first financial platform using modern data tools and machine learning techniques. Roles and Responsibilities:. Design, develop, and deploy machine learning models to assess credit and fraud risk across multiple products including savings accounts, lending, and credit cards. Build and enhance risk scoring systems leveraging structured and unstructured data from internal and alternative sources. Collaborate with strategy and product teams to implement model-driven strategies across the customer lifecycle—acquisition, underwriting, transaction monitoring, limit management, and collections. Continuously monitor model performance, recalibrate as needed, and generate insights to refine decision-making processes. Lead deep dives into complex datasets to identify fraud patterns, emerging credit risk segments, and opportunities for credit expansion. Develop robust validation frameworks and champion model governance best practices in compliance with internal and regulatory standards. Partner with engineering teams to integrate risk models into production systems, ensuring scalability and real-time decisioning. What is needed for this role: 2+ years of hands-on experience in data science and machine learning, preferably in credit or fraud risk within retail financial services. Proven ability to build and deploy predictive models using Python (e.g., scikit-learn, XGBoost) and strong data manipulation skills using SQL. Exposure to risk analytics across credit cards, personal loans, or savings products is a strong plus. Solid understanding of statistical modeling, supervised/unsupervised learning techniques, and model performance evaluation. Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Economics, or related disciplines. Strong problem-solving mindset with the ability to translate business challenges into scalable data solutions. Why you should work with us: We are the ideal workplace for individuals with a founders mentality, and we place a high regard on those who take ownership and see projects through to completion. We take pleasure in tackling meaningful problems by understanding pain points and developing intuitive experiences that delight customers. Emphasizing consent over consensus, we appreciate those who can participate in healthy conflict and are able to commit to every decision as if it were their own. In our relentless pursuit of excellence, we consistently set higher standards. If you crave continuous learning, growth, and improvement in a dynamic environment, choosing Jupiter is the right move. Our Process: We raise the bar with each hire - and evaluate our candidates to build a team of like-minded, passionate, ambitious owners. Once you apply you’re most likely to go through the following hiring process, certain roles may require more rounds. But here’s the gist - The Intro: Our recruitment team goes through all the applications we receive to find the best fit. We look for skills that would be the perfect addition to our team, and past work that can vouch for it. Two Way Street: An interview with the hiring manager. Do you like the role? What are your expectations? These are the answers we seek. Pro-tip: Ask lots of questions. Assignments may be given. Culture Matters: We don’t just value the skills we bring, we value the people we bring. This round is to see if you fit our culture & for you to find out if it works for you too. If yes, then we’re in business. If not, until next time! The Offer: The most crucial step - as far as we’re concerned. We roll out offers if we find a candidate has met all our expectations and can be a part of our crew! Want to know more about us? Hop onto the links below: Our values Our Team Our Journey What people are saying about us: - Funding Rupay Card Feature launch- Magic Spends Jupiter Money gets RBI nod for issuing PPI Sounds like you’d fit right in? Apply to our job!

Team: Data & Decision Science (D&DS) Experience: 5–8 years Location: Remote (India) Do you want to help transform the global economy? Join the movement disrupting the financial world and changing how businesses gain access to the working capital they need to grow. As the largest online platform for working capital, we serve over one million businesses in 160 countries, representing more than $10.5 trillion in annual sales. Headquartered in Kansas City, C2FO has more than 500 employees worldwide, with operations throughout Europe, India, Asia Pacific, and Australia. Here at C2FO, we value the quality of our technical solutions and are passionate about building the right thing, the right way to best solve the problem at hand. But beyond that, we also value our employees' work-life balance and promote a continuous learning culture. We host bi-annual hackathons, have multiple book clubs focused on constant growth, and embrace a remote-first working environment. If you want to work at a place where your voice will be heard and can make a real impact, C2FO is the place for you. About C2FO’s Data & Decision Science Team The Data & Decision Science (D&DS) team is one of the most dynamic and cross-functional teams at C2FO. It comprises four pillars: Data Engineering, Data Science & Analytics, Data Operations, and Business Intelligence. Spread across India and the US, our teams power C2FO’s global growth by building scalable, high-quality data solutions and driving data-backed innovation. We manage the full lifecycle of data — from architecture and governance to advanced modeling, business intelligence, and AI. Our team enables smarter decisions, deeper insights, and practical experimentation across C2FO’s ecosystem. About The Role We are looking for a Senior Data Scientist who thrives at the intersection of business impact and technical rigor. This role offers the opportunity to work on a wide variety of problems — from traditional ML (forecasting, credit scoring, churn prediction) to cutting-edge applications of large language models (LLMs) in customer engagement and retention. You’ll be part of a fast-paced, collaborative environment, where initiative, ownership, and curiosity are rewarded. Key Responsibilities Build ML models and scalable data solutions for business-critical problems like dynamic discounting, customer retention, LTV prediction, credit scoring, and more Design, experiment, and iterate quickly on MVPs that solve real business pain points Work cross-functionally to translate ambiguous business challenges into data science problems Collaborate with Data Engineering and Data Governance to ensure robust data validation and quality frameworks Conduct deep-dive analyses to extract actionable insights from large, complex datasets Contribute to a culture of learning, innovation, and experimentation What We’re Looking For 5+ years of hands-on experience in data science or applied machine learning Strong foundation in mathematics, statistics, and ML concepts Experience building and deploying ML models in production environments Proficiency in Python and data manipulation tools (SQL, Pandas) Familiarity with libraries like Scikit-learn, XGBoost, PyTorch, etc. Experience in hypothesis testing and experimentation frameworks A pragmatic mindset: build fast, learn fast, iterate fastExceptional problem-solving, communication, and stakeholder management skills Bonus: experience in fintech or financial services Benefits At C2FO, we care for our customers and people – the vital human capital that helps our customers thrive. That's why we offer a comprehensive benefits package, flexible work options for work/life balance, volunteer time off, and more. Learn more about our benefits here. Commitment to Diversity and Inclusion As an Equal Opportunity Employer, we value diversity and equality and empower our team members to bring their authentic selves to work daily. We recognize the power of inclusion, emphasizing that each team member was chosen for their unique ability to contribute to the overall success of our mission. Our goal is to create a workplace that reflects the communities we serve and our global, multicultural clients. We do not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment decisions are based on qualifications, merit, and business needs. Show more Show less

About VOIS VO IS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value and enhancing quality and efficiency across 28 countries, and operating from 7 locations: Albania, Egypt, Hungary, India, Romania, Spain and the UK. Over 29,000 highly skilled individuals are dedicated to being Vodafone Group’s partner of choice for talent, technology, and transformation. We deliver the best services across IT, Business Intelligence Services, Customer Operations, Business Operations, HR, Finance, Supply Chain, HR Operations, and many more. Established in 2006, VO IS has evolved into a global, multi-functional organisation, a Centre of Excellence for Intelligent Solutions focused on adding value and delivering business outcomes for Vodafone. About VOIS India In 2009, VO IS started operating in India and now has established global delivery centres in Pune, Bangalore and Ahmedabad. With more than 14,500 employees, VO IS India supports global markets and group functions of Vodafone, and delivers best-in-class customer experience through multi-functional services in the areas of Information Technology, Networks, Business Intelligence and Analytics, Digital Business Solutions (Robotics & AI), Commercial Operations (Consumer & Business), Intelligent Operations, Finance Operations, Supply Chain Operations and HR Operations and more. Job Description Big Data Handling: Passion and attitude to learn new data practices and tools (ingestion, transformation, governance, security & privacy), on both on-prem and Cloud (AWS preferable). Influences and contributes to innovative ways of unlocking value through companywide and external data Diagnostic Models Experience with diagnostic system using decision theory and causal models (including tools like probability, DAG, ADMG, Deterministic SME, etc) to predict the effects of an action to improve insight-led decisions. Able to productize the diagnostic systems built for reuse. Predictive & Prescriptive Analytics Models Expert in AI solutions - ML, DL, NLP, ES, RL etc. Should be able to build robust prescriptive learning systems that are scalable, real-time. Should be able to determine "Next Best Action" following Prescriptive Analytics. Autonomous Cognitive Systems Drive Autonomous system utility and continuously improve precision through creating the stable learning environment. Should be able to build Intelligent Autonomous Systems to prescribe proactive actions based on ML predictions and solicit feedback from the support functions with minimal human involvement. Big Data Tech, Environments & Frameworks Advanced applications of CNNs, RNNs, MLPs, Deep learning. Excellent application of machine learning and deep learning packages like tensorflow, pytorch, scikit, numpy, pandas, statsmodels theano, XGBoost etc. Demonstrated superior deep learning algorithms/framework. At least 1 certification in AWS will be preferred. Programming: Python, R, SQL Frameworks: TensorFlow, Keras, Scikit-learn Visualization: Tableau, Power BI Cloud: AWS, Azure Statistical Modeling: Regression, classification, clustering, time series Soft Skills: Communication, stakeholder management, problem-solving VOIS Equal Opportunity Employer Commitment India VO IS is proud to be an Equal Employment Opportunity Employer. We celebrate differences and we welcome and value diverse people and insights. We believe that being authentically human and inclusive powers our employees’ growth and enables them to create a positive impact on themselves and society. We do not discriminate based on age, colour, gender (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, race, religion, sexual orientation, status as an individual with a disability, or other applicable legally protected characteristics. As a result of living and breathing our commitment, our employees have helped us get certified as a Great Place to Work in India for four years running. We have been also highlighted among the Top 10 Best Workplaces for Millennials, Equity, and Inclusion , Top 50 Best Workplaces for Women , Top 25 Best Workplaces in IT & IT-BPM and 10th Overall Best Workplaces in India by the Great Place to Work Institute in 2024. These achievements position us among a select group of trustworthy and high-performing companies which put their employees at the heart of everything they do. By joining us, you are part of our commitment. We look forward to welcoming you into our family which represents a variety of cultures, backgrounds, perspectives, and skills! Apply now, and we’ll be in touch! Show more Show less

We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that is bold, industrious and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration and empathy. To explore exciting opportunities at the convergence of healthcare and technology, check out www.careers.indegene.com. What if we told you that you can move to an exciting role in an entrepreneurial organization without the usual risks associated with it? We understand that you are looking for growth and variety in your career at this point and we would love for you to join us in our journey and grow with us. At Indegene, our roles come with the excitement you require at this stage of your career with the reliability you seek. We hire the best and trust them from day 1 to deliver global impact, handle teams and be responsible for the outcomes while our leaders support and mentor you. We are a profitable rapidly growing global organization and are scouting for the best talent for this phase of growth. With us, you are at the intersection of two of the most exciting industries of healthcare and technology. We offer global opportunities with fast-track careers while you work with a team that is fueled by purpose. The combination of these will lead to a truly differentiated experience for you. If this excites you, then apply below. Role: Senior Analyst - Data Science Descriptions: We are looking for a results-driven and hands-on Lead Data Scientist / Analyst with 56 years of experience to lead analytical solutioning and model development in the pharmaceutical commercial analytics domain. The ideal candidate will play a central role in designing and deploying Decision Engine frameworks, implementing advanced analytics solutions, and mentoring junior team members. Key Responsibilities Partner with cross-functional teams and client stakeholders to gather business requirements and translate them into robust ML/analytical solutions. Design and implement Decision Engine workflows to support Next Best Action (NBA) recommendations in omnichannel engagement strategies. Analyze large and complex datasets across sources like APLD, sales, CRM, call plans, market share, patient claims, and segmentation data. Perform ad hoc and deep-dive analyses to address critical business questions across commercial and medical teams. Develop, validate, and maintain predictive models for use cases such as patient journey analytics, HCP targeting, sales forecasting, risk scoring, and marketing mix modeling. Implement MLOps pipelines using Dataiku, Git, and AWS services to support scalable and repeatable deployment of analytics models. Ensure data quality through systematic QC checks, test case creation, and validation frameworks. Lead and mentor junior analysts and data scientists in coding best practices, feature engineering, model interpretability, and cloud-based workflows. Stay up to date with industry trends, regulatory compliance, and emerging data science techniques relevant to life sciences analytics. Must Have 5 years of hands-on experience in pharmaceutical commercial analytics, with exposure to cross-functional brand analytics, omnichannel measurement, and ML modeling. At least 3 years of experience developing and deploying predictive models and ML pipelines in real-world settings. Proven experience with data platforms such as Snowflake, Dataiku, AWS, and proficiency in PySpark, Python, and SQL. Experience with MLOps practices, including version control, model monitoring, and automation. Strong understanding of pharmaceutical data assets (e.g., APLD, DDD, NBRx, TRx, specialty pharmacy, CRM, digital engagement). Proficiency in ML algorithms (e.g., XGBoost, Random Forest, SVM, Logistic Regression, Neural Networks, NLP). Experience in key use cases: Next Best Action, Recommendation Engines, Attribution Models, Segmentation, Marketing ROI, Collaborative Filtering. Hands-on expertise in building explainable ML models and using tools for model monitoring and retraining. Familiarity with dashboarding tools like Tableau or PowerBI is a plus. Strong communication and documentation skills to effectively convey findings to both technical and non-technical audiences. Ability to work in a dynamic, fast-paced environment and deliver results under tight timelines. EQUAL OPPORTUNITY Indegene is proud to be an Equal Employment Employer and is committed to the culture of Inclusion and Diversity. We do not discriminate on the basis of race, religion, sex, colour, age, national origin, pregnancy, sexual orientation, physical ability, or any other characteristics. All employment decisions, from hiring to separation, will be based on business requirements, the candidates merit and qualification. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristics. Locations - Bangalore, KA, IN Show more Show less

Working as an AI/ML Engineer at Navtech, you will: * Design, develop, and deploy machine learning models for classification, regression, clustering, recommendations, or NLP tasks. Clean, preprocess, and analyze large datasets to extract meaningful insights and features. Work closely with data engineers to develop scalable and reliable data pipelines. Experiment with different algorithms and techniques to improve model performance. Monitor and maintain production ML models, including retraining and model drift detection. Collaborate with software engineers to integrate ML models into applications and services. Document processes, experiments, and decisions for reproducibility and transparency. Stay current with the latest research and trends in machine learning and AI. Who Are We Looking for Exactly? * 2–4 years of hands-on experience in building and deploying ML models in real-world applications. Strong knowledge of Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar. Experience with data preprocessing, feature engineering, and model evaluation techniques. Solid understanding of ML concepts such as supervised and unsupervised learning, overfitting, regularization, etc. Experience working with Jupyter, pandas, NumPy, and visualization libraries like Matplotlib or Seaborn. Familiarity with version control (Git) and basic software engineering practices. You consistently demonstrate strong verbal and written communication skills as well as strong analytical and problem-solving abilities You should have a master’s degree /Bachelors (BS) in computer science, Software Engineering, IT, Technology Management or related degrees and throughout education in English medium. We’ll REALLY love you if you: * Have knowledge of cloud platforms (AWS, Azure, GCP) and ML services (SageMaker, Vertex AI, etc.) Have knowledge of GenAI prompting and hosting of LLMs. Have experience with NLP libraries (spaCy, Hugging Face Transformers, NLTK). Have familiarity with MLOps tools and practices (MLflow, DVC, Kubeflow, etc.). Have exposure to deep learning and neural network architectures. Have knowledge of REST APIs and how to serve ML models (e.g., Flask, FastAPI, Docker). Why Navtech? * Performance review and Appraisal Twice a year. Competitive pay package with additional bonus & benefits. Work with US, UK & Europe based industry renowned clients for exponential technical growth. Medical Insurance cover for self & immediate family. Work with a culturally diverse team from different geographies. About Us Navtech is a premier IT software and Services provider. Navtech’s mission is to increase public cloud adoption and build cloud-first solutions that become trendsetting platforms of the future. We have been recognized as the Best Cloud Service Provider at GoodFirms for ensuring good results with quality services. Here, we strive to innovate and push technology and service boundaries to provide best-in-class technology solutions to our clients at scale. We deliver to our clients globally from our state-of-the-art design and development centers in the US & Hyderabad. We’re a fast-growing company with clients in the United States, UK, and Europe. We are also a certified AWS partner. You will join a team of talented developers, quality engineers, product managers whose mission is to impact above 100 million people across the world with technological services by the year 2030. Navtech is looking for a AI/ML Engineer to join our growing data science and machine learning team. In this role, you will be responsible for building, deploying, and maintaining machine learning models and pipelines that power intelligent products and data-driven decisions. Show more Show less

About Kinaxis: About Kinaxis Elevate your career journey by embracing a new challenge with Kinaxis. We are experts in tech, but it’s really our people who give us passion to always seek ways to do things better. As such, we’re serious about your career growth and professional development, because People matter at Kinaxis. In 1984, we started out as a team of three engineers based in Ottawa, Canada. Today, we have grown to become a global organization with over 2000 employees around the world, and support 40,000+ users in over 100 countries. As a global leader in end-to-end supply chain management, we enable supply chain excellence for all industries. We are expanding our team in Chennai and around the world as we continue to innovate and revolutionize how we support our customers. Our journey in India began in 2020 and we have been growing steadily since then! Building a high-trust and high-performance culture is important to us and we are proud to be Great Place to Work® CertifiedTM. Our state-of-the-art office, located in the World Trade Centre in Chennai, offers our growing team space for expansion and collaboration. About the team: Location Chennai, India About the team The team is responsible for applying machine learning algorithms to develop intelligent supply chains. The uniqueness of the team is that it performs at the intersection of technology and real business problems. You will contribute to the product that delights customers world-wide! About the role: What you will do If you love solving complex problems, analyzing complex datasets, finding insights from data, creating data model and learning new technologies, this role is for you. As a senior software developer, you are passionate about shipping large-scale software systems in a fast-paced environment but can balance longer term issues such as maintainability, scalability, and quality. You are an experienced software engineer who is passionate about delivering software that supports and facilitates business operations of ML & AI solutions. You have a strong understanding of Cloud technologies and Cloud agnostic software architecture and have experience troubleshooting high scale solutions that are deployed and upgraded on a regular cadence. You have a passion for software reliability and know how to ensure user needs are met through cross-functional stakeholder understanding and engagement. You enjoy understanding both the details of the use cases that end-users are performing using the solution as well as the architecture and implementation of the system end to end. You have a strong interest in resolving issues as well as designing effective methods for troubleshooting, preventing, and debugging problems in software systems, getting to the root cause of issues, meeting the users’ needs and influencing the product development roadmap. You are excited about finding ways to develop product capabilities and tools that increase robustness of the user experience, reduce the cost of troubleshooting, or reduce the time required to address issues. You are fluent in Python, have experience working with distributed computing, big data frameworks and are very knowledgeable about Kubernetes and Docker. You also have experience working with and building Machine Learning pipelines and models. You have the ability and enthusiasm to learn new technologies whether they are infrastructure or language or platform,and easily adapt to change. You excel as a team player, a quick starter, and a problem solver. You thrive in cross-functional teams, actively listening and contributing to discussions. Your expertise lies in engineering solutions for complex machine learning challenges, developing Python-based applications, containerizing apps with Docker, orchestrating container swarms in Kubernetes, and building Argo Workflows. These efforts play a key role in creating ML software systems that deliver critical value to the business and its customers. What we are looking for We're looking for a highly experienced and self-driven Senior Machine Learning or Data Science Developer to join our growing team. This role requires a strong mix of data science expertise, software engineering skills, and problem-solving ability to build scalable, production-grade solutions. Education & Experience: Bachelor’s or master’s degree in computer science, Software Engineering, Data Science, or a related field, or equivalent practical experience. 10–15 years of relevant industry experience. At least 5 years of hands-on experience in building and deploying Machine Learning or Data Science solutions in a production environment. Technologies we use Strong programming skills in Python, with deep expertise in Pandas, NumPy, and major ML libraries (Scikit-learn, XGBoost, LightGBM, etc.). Experience with developing REST APIs using frameworks such as Flask or FastAPI. Solid experience working with Docker, Kubernetes, Helm, and Argo Workflows in production environments. Experience with CI/CD pipelines, preferably using GitHub Actions or similar tools. Proficiency in version control systems like Git/GitHub. Hands-on experience working with cloud platforms such as Azure, GCP, or AWS. Experience with distributed computing frameworks like Spark, and platforms like Azure Databricks or AWS EMR. Machine Learning Expertise: Solid understanding of the end-to-end ML lifecycle: data preparation, feature engineering, model training, hyperparameter tuning, model evaluation, and deployment. Experience working with structured and unstructured data, large-scale datasets, and optimizing pipelines for performance and scalability. Ability to write modular, testable, and maintainable code for ML workflows. Soft Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Proven problem-solving skills and a passion for debugging and troubleshooting complex issues. Strong organizational skills with an ability to manage multiple tasks/projects simultaneously. Nice to Have Domain knowledge in Supply Chain, especially in Demand Planning, CPG, or Manufacturing industries. Understanding of how business drivers (e.g., pricing, promotions, seasonality, weather patterns) influence demand. Experience working with time series forecasting or predictive modeling in operational contexts. Familiarity with MLFlow, DVC, or other ML experiment tracking and versioning tools. Exposure to ML model monitoring, or model explainability frameworks. #Intermediate #Full-time #LI-RJ1 Why join Kinaxis?: Work With Impact: Our platform directly helps companies power the world’s supply chains. We see the results of what we do out in the world every day—when we see store shelves stocked, when medications are available for our loved ones, and so much more. Work with Fortune 500 Brands: Companies across industries trust us to help them take control of their integrated business planning and digital supply chain. Some of our customers include Ford, Unilever, Yamaha, P&G, Lockheed-Martin, and more. Social Responsibility at Kinaxis: Our Diversity, Equity, and Inclusion Committee weighs in on hiring practices, talent assessment training materials, and mandatory training on unconscious bias and inclusion fundamentals. Sustainability is key to what we do and we’re committed to net-zero operations strategy for the long term. We are involved in our communities and support causes where we can make the most impact. People matter at Kinaxis and these are some of the perks and benefits we created for our team: Flexible vacation and Kinaxis Days (company-wide day off on the last Friday of every month) Flexible work options Physical and mental well-being programs Regularly scheduled virtual fitness classes Mentorship programs and training and career development Recognition programs and referral rewards Hackathons For more information, visit the Kinaxis web site at www.kinaxis.com or the company’s blog at http://blog.kinaxis.com. Kinaxis welcomes candidates to apply to our inclusive community. We provide accommodations upon request to ensure fairness and accessibility throughout our recruitment process for all candidates, including those with specific needs or disabilities. If you require an accommodation, please reach out to us at recruitmentprograms@kinaxis.com. Please note that this contact information is strictly for accessibility requests and cannot be used to inquire about application statuses. Kinaxis is committed to ensuring a fair and transparent recruitment process. We use artificial intelligence (AI) tools in the initial step of the recruitment process to compare submitted resumes against the job description, to identify candidates whose education, experience and skills most closely match the requirements of the role. After the initial screening, all subsequent decisions regarding your application, including final selection, are made by our human recruitment team. AI does not make any final hiring decisions.

About At Deloitte, we do not offer you just a job, but a career in the highly sought-after risk management field. We are business leaders in the risk market and work with a vision to make the world more prosperous, trustworthy, and safe. Our clients, primarily based outside of India, are large, complex organizations that constantly evolve and innovate to build better products and services. In the process, they encounter various risks and the work we do to help them address these risks is increasingly important to their success – and to the strength of the economy and public security. By joining us, you will get to work with diverse teams of professionals who design, manage, and implement risk-centric solutions across a variety of domains. In the process, you will gain exposure to the challenges related to risk management faced in today’s world by organizations across a range of industry sectors and become subject matter experts in those areas. Our Risk and Financial Advisory services professionals help organizations effectively navigate business risks and opportunities – from strategic, reputation, and financial risks to operational, cyber, and regulatory risks – to gain competitive advantage. We apply our The Team Within R&LS, Deloitte Model Risk Management (MRM) is one of the services we offer to our clients where we help them manage their risks around model usage. The team is comprised of professionals with diverse backgrounds, including Masters in Statistics, Mathematics, Physics, Finance, Financial Engineering and PhDs in various quantitative fields, etc. Our team is focused on qualitative assessment and quantitative modeling in the areas of Market Risk, Credit Risk, Operational Risk, Liquidity Risk, Fraud Risk as per regulatory guidelines like CCAR/Stress Testing, BASEL II.5 / III in US and CRD IV/CRR in EMEA regulations. The team also does valuation of complex financial products such as derivatives and structured products. Our value proposition includes industry, financial accounting and business process knowledge, proven methodologies that include risk and control concepts, deep expertise in advanced quantitative, data extraction, data mining and analytical skills. Work you’ll do The key job responsibilities will be to: Develop and maintain Financial Crime models, including AML Feeder models, Sanction Screening models through statistical analysis, and generate the necessary documentation Solve data analytical problems in risk management, identify new business insights and opportunities from data, and enhance risk management tools. Apply conceptual and quantitative depth in modeling methodologies and concepts for risk models for banks as required by regulatory guidance. Apply strong analytical and computer skills including experience with statistical and quantitative analysis technical tools such as: SAS, Python, R, SQL. Explain difficult statistical modeling concepts to diverse, non-quantitative client contacts and to experts at various clients. Required skills Familiarity with mathematics or statistical concepts like regression, classification, time series, hypothesis testing, distribution analysis, ATL/BTL testing, performance monitoring etc. Familiarity with prevalent AI/ML techniques including ANNs, Decision Trees and Ensemble techniques like XGBoost Familiarity with vendor-based transaction monitoring and sanction screening models. Experience in Anti-Financial Crime use cases involving Event Processor Next Generation, Quantifind and Customer Risk Assessment Experience in Financial Crime Case Generation Analytics Strong programming skills in R, Python, SAS, SQL etc. Proficient in deploying datasets for production environments and data calibration Experience in executive and technical report writing Understanding of AML and sanction screening regulatory environment Strong organizational and time management skills, with the ability to manage multiple priorities Ability to analyze complex issues and develop effective solutions Flexible to work on extended shifts overlapping with US/UK counterparts. Preferred skills Strong data science foundation Experience working with a Bank / Consultative environment Qualification Bachelor’s/Master’s/PhD degree How you’ll grow At Deloitte, we’ve invested a great deal to create a rich environment in which our professionals can grow. We want all our people to develop in their own way, playing to their own strengths as they hone their leadership skills. And, as a part of our efforts, we provide our professionals with a variety of learning and networking opportunities—including exposure to leaders, sponsors, coaches, and challenging assignments— to help accelerate their careers along the way. No two people learn in the same way. So, we provide a range of resources including live classrooms, team-based learning, and eLearning. DU: The Leadership Center in India, our state-of-the-art, world-class learning Center in the Hyderabad offices is an extension of the Deloitte University (DU) in Westlake, Texas, and represents a tangible symbol of our commitment to our people’s growth and development. Explore DU: The Leadership Center in India. Deloitte’s culture Our positive and supportive culture encourages our people to do their best work every day. We celebrate individuals by recognizing their uniqueness and offering them the flexibility to make daily choices that can help them to be healthy, centered, confident, and aware. Deloitte is committed to achieving diversity within its workforce, and encourages all qualified applicants to apply, irrespective of gender, age, sexual orientation, disability, culture, religious and ethnic background. We offer well-being programs and are continuously looking for new ways to maintain a culture that is inclusive, invites authenticity, leverages our diversity, and where our people excel and lead healthy, happy lives. Learn more about Life at Deloitte. Corporate citizenship Deloitte is led by a purpose: to make an impact that matters. This purpose defines who we are and extends to relationships with Deloitte’s clients, our people and our communities. We believe that business has the power to inspire and transform. We focus on education, giving, skill-based volunteerism, and leadership to help drive positive social impact in our communities. Learn more about Deloitte’s impact on the world. Recruiting tips Finding the right job and preparing for the recruitment process can be tricky. Check out tips from our Deloitte recruiting professionals to set yourself up for success. Check out recruiting tips from Deloitte recruiters. Benefits We believe that to be an undisputed leader in professional services, we should equip you with the resources that can make a positive impact on your well-being journey. Our vision is to create a leadership culture focused on the development and well-being of our people. Here are some of our benefits and programs to support you and your family’s well-being needs. Eligibility requirements may be based on role, tenure, type of employment and/ or other criteria. Learn more about what working at Deloitte can mean for you. Our people and culture Our people and our culture make Deloitte a place where leaders thrive. Get an inside look at the rich diversity of background, education, and experiences of our people. What impact will you make? Check out our professionals’ career journeys and be inspired by their stories. Professional development You want to make an impact. And we want you to make it. We can help you do that by providing you the culture, training, resources, and opportunities to help you grow and succeed as a professional. Learn more about our commitment to developing our people. Recruiting tips From developing a stand out resume to putting your best foot forward in the interview, we want you to feel prepared and confident as you explore opportunities at Deloitte. Check out recruiting tips from Deloitte recruiters. Benefits At Deloitte, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Deloitte can mean for you. Our people and culture Our inclusive culture empowers our people to be who they are, contribute their unique perspectives, and make a difference individually and collectively. It enables us to leverage different ideas and perspectives, and bring more creativity and innovation to help solve our clients' most complex challenges. This makes Deloitte one of the most rewarding places to work. Our purpose Deloitte’s purpose is to make an impact that matters for our people, clients, and communities. At Deloitte, purpose is synonymous with how we work every day. It defines who we are. Our purpose comes through in our work with clients that enables impact and value in their organizations, as well as through our own investments, commitments, and actions across areas that help drive positive outcomes for our communities. Professional development From entry-level employees to senior leaders, we believe there’s always room to learn. We offer opportunities to build new skills, take on leadership opportunities and connect and grow through mentorship. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. Requisition code: 303601

Join our Team About this opportunity Ericsson is a leading provider of telecommunications equipment and services to mobile and fixed network operators globally. We are seeking a highly skilled and experienced Data Scientist to join our dynamic team at Ericsson. As a Data Scientist, you will be responsible for leveraging advanced analytics and machine learning techniques to drive actionable insights and solutions for our telecom domain. This role requires a deep understanding of data science methodologies, strong programming skills, and proficiency in cloud-based environments. What you will do Develop and deploy machine learning models for various applications including chat-bot, XGBoost, random forest, NLP, computer vision, and generative AI. Utilize Python for data manipulation, analysis, and modeling tasks. Proficient in SQL for querying and analyzing large datasets. Experience with Docker and Kubernetes for containerization and orchestration of applications. Basic knowledge of PySpark for distributed computing and data processing. Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions. Deploy machine learning models into production environments and ensure scalability and reliability. Preferably have experience working with Google Cloud Platform (GCP) services for data storage, processing, and deployment. Experience in analysing complex problems and translate it into algorithms. Backend development in Rest APIs using Flask, Fast API Deployment experience with CI/CD pipelines Working knowledge of handling data sets and data pre-processing through PySpark Writing queries to target Casandra, PostgreSQL database. Design Principles in application development. The Skills You Bring Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree or PhD is preferred. 3-7 years of experience in data science and machine learning roles, preferably within the telecommunications or related industry. Proven experience in model development, evaluation, and deployment. Strong programming skills in Python and SQL. Familiarity with Docker, Kubernetes, and PySpark. Solid understanding of machine learning techniques and algorithms. Experience working with cloud platforms, preferably GCP. Excellent problem-solving skills and ability to work independently as well as part of a team. Strong communication and presentation skills, with the ability to explain complex analytical concepts to non-technical stakeholders. Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Bangalore Req ID: 763993

Job Summary: We are seeking an experienced and motivated Machine Learning Engineer with 3-5 years of experience in designing, developing, and deploying machine learning models. The ideal candidate must be well-versed in Python, SQL/MySQL, ML libraries, and cloud deployment using Google Cloud Platform (GCP). This role is ideal for candidates passionate about solving real-world problems using AI and ML technologies. Key Responsibilities: Build, train, evaluate, and deploy scalable machine learning models. Perform data preprocessing, feature engineering, and pipeline development. Design end-to-end ML workflows from model development to deployment on GCP. Leverage GCP tools such as Vertex AI, BigQuery, Cloud Functions, AI Platform, etc. Work with SQL/MySQL databases for data extraction and manipulation. Collaborate with cross-functional teams including data engineers, software developers, and business stakeholders. Monitor and optimize deployed models for performance and accuracy. Ensure model reproducibility, versioning, and documentation. Required Skills: Strong proficiency in Python and popular ML libraries (scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, Pandas, NumPy). Experience with SQL and MySQL. Solid understanding of ML algorithms and data handling techniques. Hands-on experience with GCP services: Vertex AI BigQuery Cloud Storage AI Platform Cloud Functions Experience in model deployment using Flask, FastAPI, or similar frameworks. Proficient in data visualization using Matplotlib, Seaborn, or similar tools. Familiarity with Git, CI/CD, and Agile practices. Preferred Qualifications: GCP Certification (e.g., Professional Machine Learning Engineer or Data Engineer). Experience with ML Ops tools. Exposure to Docker and Kubernetes. Familiarity with Big Data tools like Apache Spark or Hadoop. Perks & Benefits: 5-day working week Competitive salary and performance-based incentives Learning & development opportunities Dynamic and growth-driven work environment Job Type: Full-time Pay: ₹600,000.00 - ₹800,000.00 per month Schedule: Day shift Work Location: In person