3930 R Jobs - Page 21

Job Description: As an Analyst/Sr Analyst for Model Monitoring and Implementation at Northern Trust, you will play a vital role within the Model Strategy & Data Analytics team. Your primary responsibility will be to monitor and implement various models such as PPNR, Credit Risk, Operational Risk, and Market Risk models. This individual contributor role will involve tasks throughout the model lifecycle, including monitoring, recalibration, and implementation. You will also be involved in developing and maintaining monitoring tools using SAS for CCAR, Basel, and CECL purposes. Your key responsibilities will include monitoring, recalibrating, and implementing models such as CCAR models (PD/EAD/LGD), CECL models (PD/EAD/LGD), Basel models (PD/EAD/LGD), operational risk analytics models, and PPNR models. You will evaluate existing monitoring tools, assess development needs, and ensure compliance with different regulations such as CCAR, CECL, Basel, and IFRS9. Additionally, you will conduct analysis, interact with committees and senior management, and provide technical expertise to enhance the overall risk framework. To qualify for this role, you should have a Master's degree in Statistics, Economics, Mathematics, or an advanced degree in a quantitative area. You must possess strong knowledge of BASEL, CCAR, DFAST, CECL, and SR-11/7, along with at least 1 year of hands-on experience in monitoring, validation, or model building. Proficiency in R, SAS, Matlab, advanced Excel techniques, and VBA programming is required, with SAS being preferred. Strong quantitative skills, multitasking abilities, organizational skills, and excellent communication skills in English are also essential. Joining Northern Trust means being part of a flexible and collaborative work culture that encourages movement within the organization and offers opportunities for professional growth. As a company committed to serving the communities it operates in, Northern Trust provides a workplace with a greater purpose. If you are excited about this role and the prospect of working with us, we encourage you to apply today and discuss your flexible working requirements to achieve greater success together.,

You will play a crucial role as the Lead Analytics Consultant in the Data and Analytics Services team at Sun Life. Your primary responsibility will be to create innovative visual analytics solutions that facilitate faster and more informed decision-making processes within the organization. Your expertise will be instrumental in advancing strategic analytics projects that cater to the needs of our business stakeholders. To excel in this role, you should have a minimum of 5 years of experience in Tableau development, including designing dashboards and decision enablement tools. Proficiency in Tableau Desktop and Server platforms, as well as SQL Programming and PL/SQL, is essential. You will be required to showcase your skills by developing a diverse range of design use cases that prioritize user experience and working in an agile development environment. Ideally, you should hold a graduate degree in Mathematics, Computer Science, Engineering, or a related field to qualify for this position. Your responsibilities will involve demonstrating visual design expertise, creating complex calculations, and implementing advanced dashboard practices in Tableau. Additionally, you should be adept at data modeling, performance tuning of Tableau Server dashboards, and designing custom landing pages for enhanced user experience. Your ability to work independently, manage engagements with business partners, and extract meaningful insights from data will be key to your success in this role. Possessing additional skills such as Tableau desktop and server certification, experience with R/Python/Matlab/SAS, and exposure to Agile or design-driven development of analytics applications will be advantageous. If you are passionate about leveraging data and analytics to drive meaningful business outcomes, this role will provide you with an exciting opportunity to make a difference in the lives of individuals, families, and communities around the world.,

As a Junior Data Analyst at our company located in Hyderabad, you will play a crucial role in our Data & Analytics team. We are looking for a motivated and intellectually curious individual with a solid foundation in data analysis, business intelligence, and critical thinking. Your responsibilities will include interpreting data, generating insights, and supporting strategic initiatives across various business units. You will collaborate with internal stakeholders to understand business requirements, work with large datasets, build dashboards, and deliver actionable insights that drive informed business decisions. Your key responsibilities will involve data extraction & transformation, reporting & dashboarding, data analysis, stakeholder collaboration, data quality & governance, as well as communication & documentation. To excel in this role, you must possess a Bachelor's degree in Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field. You should have 2-3 years of hands-on experience in data analytics or business intelligence roles. Strong analytical thinking, proficiency in SQL, experience with ETL processes, and knowledge of Excel and data visualization tools like Tableau or Power BI are essential. Excellent communication skills, attention to detail, and the ability to manage multiple priorities and deadlines are also required. Preferred or bonus skills include exposure to scripting languages like Python or R, experience with cloud platforms and tools (e.g., AWS, Snowflake, Google BigQuery), prior experience in the financial services or fintech domain, and an understanding of data modeling and warehousing concepts. In return, we offer a collaborative, inclusive, and intellectually stimulating work environment, opportunities for learning and growth through hands-on projects and mentorship, and the chance to work with data that drives real business impact.,

As a qualified candidate for the role, you should possess a total professional experience ranging from 3 to 5 years along with exceptional analytical capabilities. Your expertise should extend to working proficiently with statistical tools such as SAS, WPS, R, and CART. Holding an M.Tech, MBA, or Masters degree from renowned academic institutions with a remarkable academic record is highly desirable. Your role will involve modeling and machine learning, making it essential for you to have hands-on experience in these areas. A successful track record in managing complex analytical or scientific projects is crucial. Demonstrating strong communication, interpersonal, leadership, and team management skills is equally important. In addition to your technical competencies, you should be willing to work in an international setting and exhibit traits of a team player with good interpersonal and organizational skills. Your ability to perform effectively under pressure, meet deadlines, and communicate clearly will be key to your success in this role. Moreover, having an analytical mindset and an interest in traveling and exploring different parts of the world will be advantageous.,

As an Associate Managing Consultant in Strategy & Transformation at Mastercard's Performance Analytics division, you will be a part of the Advisors & Consulting Services group specializing in translating data into actionable insights. Your role will involve leveraging both Mastercard and customer data to design, implement, and scale analytical solutions for clients. By utilizing qualitative and quantitative analytical techniques and enterprise applications, you will synthesize analyses into clear recommendations and impactful narratives. In this position, you will manage deliverable development and workstreams on projects spanning various industries and problem statements. You will contribute to developing analytics strategies for large clients, leveraging data and technology solutions to unlock client value. Building and maintaining trusted relationships with client managers will be crucial, as you act as a reliable partner in creating predictive models and reviewing analytics end-products for accuracy, quality, and timeliness. Collaboration and teamwork play a significant role in this role, where you will be tasked with developing sound business recommendations, delivering effective client presentations, and leading team and external meetings. Your responsibilities will also include contributing to the firm's intellectual capital, mentoring junior consultants, and fostering effective working relationships with local and global teams. To be successful in this role, you should possess an undergraduate degree with experience in data and analytics, business intelligence, and descriptive, predictive, or prescriptive analytics. You should be adept at analyzing large datasets, synthesizing key findings, and providing recommendations through descriptive analytics and business intelligence. Proficiency in data analytics software such as Python, R, SQL, and SAS, as well as advanced skills in Word, Excel, and PowerPoint, are essential. Effective communication in English and the local office language, eligibility to work in the country of application, and a proactive attitude towards learning and growth are also required. Preferred qualifications for this role include additional experience working with the Hadoop framework, data visualization tools like Tableau and Power BI, and coaching junior delivery consultants. While an MBA or master's degree with a relevant specialization is not mandatory, having relevant industry expertise would be advantageous. At Mastercard, we prioritize information security, and every individual associated with the organization is expected to abide by security policies, maintain the confidentiality and integrity of accessed information, report any security violations or breaches, and complete required security trainings to ensure the protection of Mastercard's assets, information, and networks.,

As an experienced Traffic Data Scientist or Transportation Analyst, you will play a crucial role in our team by transforming raw traffic data into actionable insights. Your expertise in analyzing and modeling traffic patterns, particularly in congestion analytics, junction analysis, and predictive traffic models, will be essential in addressing real-world traffic challenges and shaping the core intelligence of our product. Your key responsibilities will include developing advanced models for congestion analytics to identify and analyze traffic congestion, analyzing complex intersections for traffic flow modeling and bottleneck identification, designing proprietary traffic network models for simulating traffic flow, creating machine learning models for predictive analytics on traffic conditions, and collaborating with the software engineering team to integrate your models for providing actionable insights to our users. To excel in this role, you should have proven experience in traffic analysis and modeling, proficiency in data analysis and programming languages like Python or R, hands-on experience with data science libraries and frameworks such as pandas, NumPy, scikit-learn, TensorFlow, or PyTorch, a solid understanding of statistical analysis and machine learning techniques, experience in building predictive models for time-series data, and familiarity with GIS and geospatial data analysis. Additionally, possessing excellent problem-solving skills, the ability to communicate and collaborate effectively in a team environment, and a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Civil Engineering (with a focus on transportation), or a related field will be advantageous for this role. Join us in leveraging your expertise to make a significant impact on traffic challenges and contribute to the overall product roadmap.,

As a Project Manager specializing in Data & Analytics, you will play a crucial role in transforming data into valuable business insights. Your primary responsibility will involve leading impactful data-driven projects spanning various business domains. Your key tasks will include driving project delivery in data engineering, business intelligence (BI), and analytics, ensuring alignment among technical and business teams, managing scope, risks, and milestones in an Agile setting, and translating business objectives into measurable data outcomes. Monitoring key performance indicators (KPIs), return on investment (ROI), and ensuring timely, high-quality project delivery will also be part of your duties. To excel in this role, you should possess a minimum of 6 years of overall experience, with at least 3 years dedicated to data/analytics project management. A deep understanding of artificial intelligence (AI), ETL pipelines, data warehousing, and visualization tools is essential. Proficiency in tools such as SQL, Power BI/Tableau, and preferably Python/R or R, along with experience working with Cloud platforms like AWS, GCP, or Azure, will be advantageous. Strong stakeholder management, planning, and budgeting skills are required, and holding certifications like PMP or PRINCE2 would be a plus. By joining our team, you will have the opportunity to make data relevant across different industries, collaborate with talented professionals from the technology and business sectors, and lead the development of solutions that drive tangible business outcomes. If you are ready to shape the future of data and have the required expertise, we encourage you to apply now or reach out for more information. Feel free to refer someone who you believe is a perfect fit for this role. #Hiring #ProjectManager #DataAnalytics #DataEngineering #BusinessIntelligence #CloudData #Leadership #TechJobs #NowHiring #AgileProjectManagement,

As the leader of the data analytics and AI team, you will play a crucial role in driving our organization towards a data-first and data-driven approach. Your primary responsibility will be to deliver and maintain smart data-driven solutions that are essential for our growth and daily operations. By accelerating the adoption of AI solutions, you will enhance efficiency, foster innovation, and gain a competitive advantage for the company. Your role will involve overseeing all aspects of new data and AI projects, from their inception to delivery, with a strong emphasis on assessing business value, ROI, and cost reduction. Your key responsibilities will include leading and developing a robust data analytics and AI team, establishing best practices and methodologies for data analytics and responsible AI initiatives, managing and overseeing AI and LLM projects, building relationships with business process owners, collaborating with internal and external stakeholders, developing advanced models and algorithms, addressing data mining performance issues, and staying updated on the latest advancements in AI and LLM technologies to improve project outcomes. Preferred skills for this role include proficiency in programming languages such as Python, R, or similar, understanding of algorithms like linear regression, logistic regression, decision trees, random forest, boosting algorithms (e.g., XGBoost), clustering techniques, and principal component analysis. Additionally, familiarity with data science concepts including statistics, probability, data transformation, visualization, storytelling, and deep learning, as well as expertise in statistical and mathematical methods and data & AI technologies/tools like ML Ops, ETL, data lakes, graph databases, NLK, and data optimization will be beneficial for success in this position.,

You are an experienced Business Analyst with a focus on Data Analytics looking to join a dynamic team in the Banking domain. You have a strong analytical mindset, business acumen, and a proven track record in data-driven decision-making. Your main responsibilities will include collaborating with business stakeholders to gather requirements, translating business needs into technical specifications, and performing in-depth data analysis using tools like SQL, Excel, and BI tools. You will also be responsible for supporting decision-making through dashboards, reports, and visualizations, as well as working closely with data engineering and BI teams for solution implementation. To excel in this role, you must have at least 6 years of experience as a Business Analyst, with a specific focus on Data Analytics in the Banking/Financial Services domain. Strong SQL skills and hands-on experience with analytical tools like Tableau, Power BI, Excel, and preferably Python/R are essential. You should also possess a deep understanding of data pipelines, KPIs, and business metrics, along with excellent communication and stakeholder management abilities. The ability to thrive in a fast-paced, agile environment is crucial. The ideal candidate will be available to join immediately or by August at the latest. Additionally, you should have strong documentation, storytelling, and data presentation skills, as well as experience collaborating with cross-functional tech and business teams. If you meet these requirements and are passionate about leveraging data to drive business insights and decisions, we would love to hear from you.,

You will be joining the Microsoft Security organization, where security is a top priority due to the increasing digital threats, regulatory scrutiny, and complex estate environments. Microsoft Security aims to make the world a safer place by providing end-to-end security solutions to empower users, customers, and developers. As a Senior Data Scientist, you will be instrumental in enhancing our security posture by developing innovative models to detect and predict security threats. This role requires a deep understanding of data science, machine learning, and cybersecurity, along with the ability to analyze large datasets and collaborate with security experts to address emerging threats and vulnerabilities. Your responsibilities will include understanding complex cybersecurity and business problems, translating them into well-defined data science problems, and building scalable solutions. You will develop and deploy production-grade AI/ML systems for real-time threat detection, analyze large datasets to identify security risks, and collaborate with security experts to incorporate domain knowledge into models. Additionally, you will lead the design and implementation of data-driven security solutions, mentor junior data scientists, and communicate findings to stakeholders. To qualify for this role, you should have experience in developing and deploying machine learning models for security applications, preferably in a Big Data or cybersecurity environment. You should be familiar with the Azure tech stack, have knowledge of anomaly detection and fraud detection, and possess expertise in programming languages such as Python, R, or Scala. A Doctorate or Master's Degree in a related field, along with 5+ years of data science experience, is preferred. Strong analytical, problem-solving, and communication skills are essential, as well as proficiency in machine learning frameworks and cybersecurity principles. Preferred qualifications include additional experience in developing machine learning models for security applications, familiarity with data science workloads on the Azure tech stack, and contributions to the field of data science or cybersecurity. Your ability to drive large-scale system designs, think creatively, and translate complex data into actionable insights will be crucial in this role.,

You will be responsible for working with a team of data scientists to oversee multiple projects. Your role will involve guiding the team in formulating, developing, and implementing models, while also engaging with business stakeholders to clarify model outcomes. With 6 to 9 years of experience, you should possess a deep understanding of Statistics and hands-on experience with Machine Learning algorithms and techniques. Proficiency in programming languages such as R/SQL and Python is essential, along with a strong background in DL frameworks like TensorFlow and Theano. Your scientific expertise should encompass real-world experience in Deep Learning, including Convolutional Neural Networks, Restricted Boltzmann Machines, and Deep Neural Networks. Your passion for solving complex analytical problems will be crucial, along with the ability to assess problems quantitatively and qualitatively. Collaboration with team members to identify and resolve challenging issues will be a key aspect of your role. Previous experience in applying Machine Learning techniques in a production environment is highly desirable. As part of your responsibilities, you will design, develop, and implement AI/Machine Learning solutions for our industry-specific data analytics platform. Creating scalable processes for collecting, manipulating, presenting, and analyzing large datasets in a production setting will be a core focus. You will define problems, handle all data aspects from acquisition to visualization, conduct feature engineering using ML algorithms, and deploy models effectively. Furthermore, you will be tasked with developing algorithm prototypes, evaluating performance metrics based on real-world datasets, and providing input and guidance to software engineers for algorithm implementation in solution/product development. To qualify for this role, you should have a minimum of 6 years of professional experience in Life Science/Pharma. A degree in Applied Mathematics, Statistics, Machine Learning, or Computer Science is required, with a preference for candidates holding a Ph.D. or MS degree.,

As the leading innovator in low-power wireless connectivity, Silicon Labs (NASDAQ: SLAB) is dedicated to building embedded technology that connects devices and enhances lives. By integrating cutting-edge technology into highly integrated SoCs, we empower device makers with the solutions, support, and ecosystems necessary for developing advanced edge connectivity applications. With our headquarters in Austin, Texas, and operations spanning over 16 countries, Silicon Labs is the trusted partner for innovative solutions in the smart home, industrial IoT, and smart cities markets. To learn more about us, visit www.silabs.com. In this role, you will lead and execute complex data science initiatives that drive high-impact business decisions. You will be responsible for developing, deploying, and communicating advanced analytical models. Additionally, you will provide technical guidance to junior data scientists and collaborate closely with cross-functional teams to achieve data-driven outcomes. Your responsibilities will include designing and implementing advanced statistical and machine learning models to solve complex business problems. You will lead full-cycle analytics projects, from problem definition to data exploration, model development, evaluation, and deployment. Collaboration with stakeholders to align data science solutions with business goals, providing technical mentorship to junior team members, and translating complex modeling outputs into actionable insights for senior leadership will also be key aspects of your role. As for qualifications and skills, we are looking for candidates with a Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Masters preferred). A minimum of 4 years of experience in data science, machine learning, or advanced analytics is required. You should have advanced proficiency in Python or R, SQL, and machine learning libraries such as scikit-learn and TensorFlow. A strong grasp of statistical analysis, experimental design, model evaluation techniques, and excellent written and verbal communication skills are essential. Experience in leading complex data projects, familiarity with cloud-based data platforms (e.g., AWS, GCP, Azure), and MLOps practices will be advantageous. Joining our team not only means being part of a highly skilled and close-knit group where every engineer's contribution is significant, but also enjoying a good work/life balance and a welcoming, fun environment. We offer benefits and perks such as Equity Rewards (RSUs), Employee Stock Purchase Plan (ESPP), insurance plans with Outpatient cover, National Pension Scheme (NPS), flexible work policy, and childcare support. If you are passionate about data science, machine learning, and advanced analytics, and are eager to make a meaningful impact in a dynamic and innovative environment, we welcome you to apply and be part of our team at Silicon Labs.,

As a Power BI Developer, you will be an integral part of our dynamic team, contributing your expertise to design, develop, and implement advanced Power BI solutions that facilitate data-driven decision-making. Your role will involve close collaboration with business stakeholders to grasp their requirements and translate them into visually appealing and high-performance Power BI reports. Your responsibilities will span various key areas, including data modeling and analysis. You will be tasked with creating robust data models, utilizing advanced DAX for complex calculations, and effectively transforming and cleaning data using Power Query. Additionally, you will develop interactive Power BI reports with diverse visualizations, optimize report performance, and enforce data access control through Row-Level Security (RLS). Furthermore, you will oversee Power BI Service administration, managing capacities, licenses, and deployment strategies while integrating Power BI with other Microsoft tools for enhanced automation and data processing. Your expertise in cloud platforms like MS Fabric, Data Factory, and Data Lake will be crucial in optimizing data pipelines and scalability. In addition to your technical responsibilities, you will engage in collaboration with stakeholders to deliver actionable insights, mentor junior team members on best practices, and provide technical leadership by ensuring adherence to standards and deploying reports to production environments. To qualify for this role, you should possess 2 to 6 years of hands-on experience with Power BI and related technologies, demonstrating proficiency in data modeling, DAX, Power Query, visualization techniques, and SQL skills. Experience in ETL processes, cloud platforms, and strong problem-solving abilities are essential. Excellent communication skills and the ability to work both independently and collaboratively are also required. Preferred qualifications include experience with R or Python for custom visual development and certification in Power BI or related technologies. Please note that this position mandates working at our (South) Bangalore office for at least 4 out of 5 days, with no remote work option available. Local candidates are preferred, and relocation assistance will not be provided. This is a full-time position based in Bangalore (South), offering a competitive salary range of 500,000-1,200,000 INR per year. If you meet the qualifications and are eager to contribute to our team, we encourage you to apply before the deadline of April 15, 2025.,

As a seasoned Data Analyst with over 10 years of experience, you will play a crucial role in the development and implementation of data analytics strategies, frameworks, and methodologies that are in line with the goals and objectives of the organization. Your primary responsibility will be to drive the identification and exploration of data-driven opportunities to optimize business performance, enhance operational efficiency, and achieve strategic objectives. You will collaborate closely with senior leaders and stakeholders to define analytical requirements, establish key performance indicators (KPIs), and develop metrics to measure business performance and progress. Additionally, you will design and implement advanced analytical models and algorithms to extract insights, uncover patterns, and make predictions using large and complex data sets. Your expertise in data analysis, statistical modeling, and machine learning techniques will be instrumental in addressing complex business problems and supporting strategic decision-making. Furthermore, you will be tasked with developing and maintaining data governance frameworks, data quality standards, and data management practices to ensure the accuracy, integrity, and consistency of data assets. In this role, you will lead cross-functional teams in the design and delivery of data visualizations, dashboards, and reports that effectively communicate insights and drive action. It will be essential for you to stay updated with emerging trends, technologies, and best practices in data analytics and provide recommendations for their adoption to enhance analytical capabilities. Mentoring and coaching junior analysts to foster their professional growth and supporting their development of advanced analytical skills will also be part of your responsibilities. You will collaborate closely with data engineering teams to ensure efficient data collection, integration, and preparation for analysis purposes. Presenting complex findings, insights, and recommendations to senior leaders and stakeholders in a clear, concise, and compelling manner will be crucial. Moreover, you will play a key role in fostering a data-driven culture within the organization by promoting the value of data, advocating for data-driven decision-making, and driving data literacy initiatives. Requirements: - Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, or Computer Science. A Master's or Ph.D. degree is strongly preferred. - 10+ years of extensive experience as a Data Analyst, with a significant portion of experience in a senior or lead role. - Proven track record of designing and implementing data analytics strategies and driving successful data-driven initiatives. - Expert proficiency in SQL for data extraction, manipulation, and analysis. - Advanced programming skills in Python/R for statistical analysis, predictive modeling, and machine learning. - In-depth knowledge of statistical analysis techniques, predictive modeling, and advanced machine learning algorithms. - Strong experience with data visualization tools such as Tableau, Power BI, or similar. - Extensive experience with data blending, preprocessing, and automation tools within PowerBi or similar. - Solid understanding of database structures, data warehousing concepts, and data governance principles. - Exceptional analytical and problem-solving skills, with the ability to tackle complex business challenges and provide innovative solutions. - Excellent leadership, strategic thinking, and stakeholder management abilities. - Exceptional communication and presentation skills, with the ability to influence and inspire stakeholders at all levels of the organization. - Proven ability to work independently, manage multiple projects, and prioritize effectively. Preferred Qualifications: - Experience in implementing data analytics solutions in cloud platforms such as AWS, Azure, or Google Cloud. - Knowledge of big data technologies such as Hadoop, Spark, or similar. - Familiarity with data science platforms and libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Strong business acumen and the ability to align data analysis efforts with organizational goals and strategies. - Experience in leading and managing cross-functional teams.,

Whether you're at the start of your career or looking to discover your next adventure, your story begins here. At Citi, you'll have the opportunity to expand your skills and make a difference at one of the world's most global banks. We're fully committed to supporting your growth and development from the start with extensive on-the-job training and exposure to senior leaders, as well as more traditional learning. You'll also have the chance to give back and make a positive impact where we live and work through volunteerism. Institutional Credit Management's (ICM) objective is to provide an integrated end-to-end credit underwriting, identification, measurement, management, monitoring, and reporting for wholesale credit businesses across the enterprise. Institutional Client Group (ICG) In-Business Quality Assurance is an integral part of the ICM organization. The ICM In-Business Quality Assurance function (QA) verifies that established standards and processes are followed and consistently applied. ICM uses the results of the quality assurance reviews to assess the quality of the group's policies, procedures, programs, and practices as they relate to the management of wholesale credit risk. The results help management identify operational weaknesses, risks associated with the function, training needs, and process deficiencies. This role would ideally be suited to someone who is an analyst within the credit risk analysis unit within the domain of Institutional Wholesale Banking. The ideal candidate will be currently working in 1st or 2nd LOD areas, in roles such as Data Analyst, Credit Analyst, or a Business analyst. This role reports to the ICM Head of In-Business Quality Assurance Head of Data Analytics. In this role, you're expected to support the In-Business Quality Assurance Head of Data Analytics to set the global strategy for and lead the implementation and ongoing delivery of a robust Data analytics and testing program for the Quality Assurance function as it relates to Wholesale Credit Risk (WCR) data governance. You will provide effective challenge on the design and operation of the data and credit processes within ICM and report any identified gaps and concerns on those through quarterly reports published to ICG senior management. You should have the ability to query and clean complex datasets from multiple sources and have deep and hands-on experience in deriving concrete insight from data and qualifying business impact. Additionally, you will develop processes and tools to monitor and analyze model performance and data accuracy, collaborate within IBQA teams and with QA Directors to provide them with analytics insights, provide oversight and guidance over the assessment of complex data-related issues, structure potential solutions, and drive effective resolution with stakeholders, support WCR IBQA team to abreast of relevant changes to rules/regulations and other industry news including regulatory findings, and support WCR IBQA Voice of the Employee (VOE) as well as diversity and inclusion initiatives. This is a hybrid role requiring office attendance 3 times a week. As a successful candidate, you'd ideally have the following skills and exposure: Analytics and Business: - Good understanding of Underwriting space with experience in Banking and Financial Services Industry. - Relevant years of experience in data analytics, modeling and analytics, internal audit, or similar functions at an investment or large commercial bank. - Good grasp of Wholesale Credit Risk and Counterparty Credit Risk Processes and organizational awareness, to evaluate findings identified through the Quality Assurance process, determine materiality, and partnering with business to drive sustainable remediation. Leadership: - Assists colleagues in identifying stretch opportunities to elevate individual and team performance and recognizes individuals based on performance. - Continuous learning and improvement mindset. - Proven culture carrier. Competencies: - Solid organizational skills with the ability and willingness to work under pressure and manage time and priorities effectively. - Written and verbal communication skills, with the ability to communicate clearly and concisely to audiences of varying levels of seniority. - A drive to learn and master new technologies and techniques. - Experience in analyzing datasets and distilling them into actionable information as well as building out end-to-end analytical process flows. - Understanding of process redesign/re-engineering and execution. - Analytical and decision-making capabilities including the ability to identify, escalate, and propose and execute solutions to complex problems. - Experience in preparing presentations for seniors. Technical: - Coding knowledge and experience with at least one programming language (Python & tableau skills or similar tools) will be an advantage. - Proven experience of agile collaborative working. - Experience working with data and deriving insights. Education: - Bachelor's or Master's Degree in Business Administration, Finance, or similar disciplines. - Data Analysis: SQL; Python; SAS; R, Alteryx. - Visualization: Tableau; QlikView; MS Power BI. - Programming language: Python. Global Benefits: We provide programs and services for your physical and mental well-being including access to telehealth options, health advocates, confidential counseling, and more. Coverage varies by country. We have a variety of programs that help employees balance their work and life, including generous paid time off packages. Working at Citi is far more than just a job. A career with us means joining a family of more than 230,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community, and make a real impact. Take the next step in your career, apply for this role at Citi today. This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.,

You will be joining EXL, a leading operations management and analytics company dedicated to helping businesses thrive in competitive and disruptive environments. Through our innovative methodologies encompassing advanced analytics, data management, digital solutions, BPO, consulting, industry best practices, and cutting-edge technology platforms, we delve deep to support companies in enhancing global operations, fostering data-driven insights, improving customer satisfaction, and effectively managing risk and compliance. EXL caters to various industries such as insurance, healthcare, banking and financial services, utilities, travel, transportation, and logistics, with a team of over 30,000 professionals located across the United States, Europe, Asia (mainly India and the Philippines), Latin America, Australia, and South Africa. In the realm of EXL Analytics, we provide actionable solutions to business challenges through statistical data mining, advanced analytics techniques, and a consultative approach. By utilizing our proprietary methodology and top-tier technology, EXL Analytics adopts an industry-specific strategy to revolutionize clients" decision-making processes and embed analytics deeply into their business operations. Our team of nearly 2,000 data scientists and analysts worldwide support client organizations in diverse areas such as risk minimization, advanced marketing strategies, pricing and CRM techniques, internal cost analysis, and optimizing resources within the organization. EXL Analytics caters to industries like insurance, healthcare, banking, capital markets, utilities, retail and e-commerce, travel, transportation, and logistics. Your role will involve being a proficient credit risk model professional with expertise in model monitoring, validation, implementation, and maintenance of regulatory models. Some of your key responsibilities will include assisting in various aspects of model risk management in alignment with regulations, conducting essential tests such as model performance evaluations, sensitivity analyses, and back-testing, collaborating with the model governance team on model development and monitoring, liaising with cross-functional teams including business stakeholders, model validation, and governance teams, delivering high-quality client services encompassing model documentation within stipulated timeframes. To excel in this role, you should have a minimum of 2+ years of experience in executing end-to-end monitoring, validation, production, and implementation of credit risk models, particularly CCAR/CECL/IFRS9 regulatory models. You should possess a strong comprehension of credit risk regulatory models, along with expertise in marketing and general analytics problems. Your ability to manage assigned projects efficiently, ensuring accuracy and timely deliverables, as well as training, coaching, and developing team members, will be crucial for success. For qualifications, you should have prior analytics experience (2+ years), preferably in the BFSI sector, with a good understanding of General Analytics and Fraud Analytics. Past experience in roles involving problem-solving and strategic initiatives is advantageous. Proficiency in SAS/SAS macros, Python, or SQL is essential, while hands-on experience in R or any other analytical software would be a plus. Strong problem-solving skills will further enhance your suitability for this role.,

As a Data Scientist at KPMG in India, you will collaborate with business stakeholders and cross-functional subject matter experts to gain a deep understanding of the business context and key questions. You will be responsible for creating Proof of Concepts (POCs) and Minimum Viable Products (MVPs), and guiding them through production deployment and operationalization. Your role will involve influencing machine learning strategy for digital programs and projects, while making solution recommendations that balance speed to market and analytical soundness. In this position, you will explore design options to assess efficiency and impact, develop approaches to enhance robustness and rigor, and develop analytical and modeling solutions using various tools such as Python, R, and TensorFlow. You will be tasked with formulating model-based solutions by integrating machine learning algorithms with other techniques like simulations, as well as designing, adapting, and visualizing solutions based on evolving requirements. Your responsibilities will also include creating algorithms to extract information from large datasets, deploying algorithms to production to identify actionable insights, and comparing results from different methodologies to recommend optimal techniques. Moreover, you will work on multiple facets of AI including cognitive engineering, conversational bots, and data science, ensuring that solutions demonstrate high levels of performance, security, scalability, and maintainability upon deployment. As a part of your role, you will lead discussions at peer reviews and utilize interpersonal skills to positively influence decision-making processes. You will provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts, making significant contributions to internal discussions on emerging practices. Additionally, you will facilitate the sharing of new ideas, learnings, and best practices across different geographies. To qualify for this position, you must hold a Bachelor of Science or Bachelor of Engineering degree at a minimum, along with 2-4 years of work experience as a Data Scientist. You should possess a blend of business focus, strong analytical and problem-solving skills, and programming knowledge. Proficiency in statistical concepts, ML algorithms, statistical/programming software (e.g., R, Python), data querying languages (e.g., SQL, Hadoop/Hive, Scala), and experience with data management tools like Microsoft Azure or AWS are essential requirements. Moreover, you should have hands-on experience in feature engineering, hyperparameter optimization, and producing high-quality code, tests, and documentation. Familiarity with Agile principles and processes, and the ability to lead, manage, and deliver business results through data scientists or professional services teams are also crucial. Excellent communication skills, self-motivation, proactive problem-solving abilities, and the capability to work both independently and in teams are vital for this role. While a Bachelor's or Master's degree in technology-related fields is preferred, possessing relevant experience in Software Engineering or Data Science is mandatory. Additionally, familiarity with AI frameworks, deep learning, computer vision, and cloud services along with proficiency in Python, SQL, Docker, and versioning tools are highly desirable. The ideal candidate will also have experience with Agent Framework, RAG Framework, AI algorithms, and other relevant technologies as mentioned in the job description.,

As a Senior Analyst - Data Analytics, you will leverage your 3+ years of experience in Data Analytics and reporting to design and build interactive dashboards and reports using Power BI and Microsoft Fabric. Your strong technical expertise in Power BI, Microsoft Fabric, Snowflake, SQL, Python, and R will be instrumental in performing advanced data analysis and visualization to support business decision-making. You will utilize your experience with Azure Data Factory, Databricks, Synapse Analytics, and AWS Glue to develop and maintain data pipelines and queries using SQL and Python. Applying data science techniques such as predictive modeling, classification, clustering, and regression, you will solve business problems and uncover actionable insights. Your hands-on experience in building and deploying machine learning models will be crucial in building, validating, and tuning machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks. Collaborating with stakeholders, you will translate business questions into data science problems and communicate findings in a clear, actionable manner. You will use statistical techniques and hypothesis testing to validate assumptions and support decision-making. Documenting data science workflows and maintaining the reproducibility of experiments and models will ensure the success of analytics projects. Additionally, you will support the Data Analytics Manager in delivering analytics projects and mentoring junior analysts. Professional certifications such as Microsoft Certified: Power BI Data Analyst Associate (PL-300), SnowPro Core Certification (Snowflake), Microsoft Certified: Azure Data Engineer Associate, and AWS Certified: Data Analytics Specialty are preferred or in progress to enhance your expertise in the field.,

As a Management Trainee in HR specializing in Artificial Intelligence based in Mumbai, you will have the opportunity to lead the transformation of traditional HR practices by leveraging data-driven and AI-enabled solutions. Your role will involve working on cutting-edge projects that delve into predictive talent analytics, AI-powered recruitment, chatbot automation, employee sentiment analysis, intelligent performance management systems, and talent management. This position is tailored for early-career professionals who possess a deep passion for both HR and technology, aspiring to revolutionize the future of work through innovation and digitalization. Your responsibilities will include collaborating with various HR Centers of Excellence (CoEs) such as Talent Acquisition, Learning & Development, and Rewards to identify opportunities where AI can enhance efficiency and effectiveness. You will be tasked with developing and implementing AI models for talent insights like attrition prediction, engagement analysis, and workforce planning. Additionally, you will support the integration and oversight of AI-driven tools such as chatbots and recommendation engines, and contribute to data collection, cleansing, and visualization for ongoing HR analytics projects. Your role will also involve staying abreast of HR Tech and AI trends to propose forward-thinking solutions to the HR leadership team, as well as participating in pilot projects, proof-of-concept tests, and vendor assessments for AI tools in HR. Furthermore, you will be responsible for documenting best practices, use cases, and insights for knowledge management purposes. To excel in this role, you should hold a B. Tech degree and an MBA/PGDM in Human Resources or equivalent from a renowned institute (expected graduation in 2025) with previous work experience. A background or coursework in Data Science, AI, Machine Learning, or HR Analytics is highly desirable. Proficiency in tools like Python, R, Power BI, Tableau, or SQL would be advantageous. An analytical mindset with a keen interest in data and emerging technologies, as well as exceptional communication, collaboration, and project management skills are essential. Your demonstrated enthusiasm for future-of-work, digital HR, or HR transformation initiatives will be a valuable asset in this role.,

The Risk division at Goldman Sachs is responsible for managing credit, market, operational risk, model risk, independent liquidity risk, and insurance across the firm. Analytics & Reporting (A&R) is a crucial group within Risk Engineering in the Risk Division of Goldman Sachs. The primary objective of this group is to provide a comprehensive view of the firm's risk profile to senior leadership, investors, and regulators. This enables them to make informed and timely risk management decisions. Risk Engineering is a team of quantitative experts responsible for producing independent risk & capital metrics for the firm. They model, produce, review, interpret, and communicate risk & capital metrics to ensure the firm adheres to its Risk Appetite and maintains the appropriate amount of Risk Capital. The insights provided by Risk Engineering are essential for the Chief Risk Officer, senior management, regulators, and other stakeholders. As a member of the A&R team, your role will involve delivering critical regulatory and risk metrics & analytics across various risk domains such as market, credit, liquidity, operational, and capital. You will be responsible for providing regular reporting, customized risk analysis, systematically generated risk reporting, and risk tools. Key Responsibilities: - Delivering regular and reliable risk metrics, analytics & insights based on a deep understanding of the firm's businesses and client activities. - Building robust, systematic & efficient workflows, processes, and procedures for the production of risk analytics for financial & non-financial risk, risk capital, and regulatory reporting. - Ensuring the quality, timeliness, and completeness of the underlying data used for producing risk analytics. Qualifications, Skills & Aptitude: - A Masters or Bachelors degree in a quantitative discipline like mathematics, physics, econometrics, computer science, or engineering. - Entrepreneurial, analytically creative, self-motivated, and team-oriented mindset. - Excellent written, verbal, and team-oriented communication skills. - Experience with programming for extract transform load (ETL) operations and data analysis using languages such as Python, Java, C++, SQL, and R. - Proficiency in developing data visualization and business intelligence solutions using tools like Tableau, Alteryx, PowerBI, and front-end technologies. - Working knowledge of the financial industry, markets, products, non-financial risk, mathematics including statistics, time series analysis, and numerical algorithms. - Minimum of 5 years of financial or non-financial risk industry experience. Goldman Sachs is a global investment banking, securities, and investment management firm committed to diversity, inclusion, and providing growth opportunities for its employees. If you believe you have the qualifications and skills for this role, we encourage you to apply and be part of our dynamic team. ,

As a Data Scientist at our company, you will be responsible for delivering end-to-end projects in the Analytics space. You must possess the skills in Big Data, Python or R to drive business results through data-based insights. Your role will involve working with various stakeholders and functional teams, discovering solutions in large data sets, and improving business outcomes. Identifying valuable data sources and collection processes will be a key part of your responsibilities. You will oversee the preprocessing of both structured and unstructured data, analyze large volumes of information to identify trends and patterns specific to the insurance industry. Building predictive models, machine-learning algorithms, and ensemble modeling will be essential tasks. You will also be required to present information using data visualization techniques and collaborate with engineering and product development teams. To excel in this role, you should have 3.5-5 years of experience in Analytics systems/program delivery, with a minimum of 2 project implementations in Big Data or Advanced Analytics. Proficiency in statistical computer languages such as R, Python, SQL, and Pyspark is necessary. Familiarity with Scala, Java, or C++ and knowledge of various machine learning techniques and advanced statistical concepts are also required. Hands-on experience with Azure/AWS analytics platforms, Databricks or similar analytical applications, business intelligence tools like Tableau, and data frameworks such as Hadoop is crucial. Strong mathematical skills, excellent communication, and presentation abilities are essential for this role. In addition to technical skills, you should have multi-industry domain experience, expertise in Python, Scala, SQL, and knowledge of Tableau/Power BI or similar self-service visualization tools. Your interpersonal and team skills should be exemplary, and any past leadership experience would be advantageous. Join our team at Accenture and leverage your expertise to drive impactful business outcomes through data-driven insights. Experience: 3.5 - 5 years of relevant experience required Educational Qualification: Graduation,

As a Machine Learning Specialist in Clinical Supply Chain, you will play a crucial role in leveraging your expertise in data science to enhance the efficiency of our clinical trial supply chain. Your responsibilities will include designing, developing, and implementing machine learning models to predict clinical supply needs, optimize inventory levels, and minimize wastage. By collaborating with various teams, such as clinical operations, supply chain, and IT, you will identify relevant data sources and seamlessly integrate machine learning solutions into existing workflows. Your key duties will involve analyzing extensive datasets from clinical trials, logistics systems, and external sources to identify trends and extract valuable insights. You will be tasked with creating tools and dashboards that facilitate real-time decision-making and scenario planning. It will also be your responsibility to ensure that the developed models adhere to performance standards, scalability requirements, and regulatory guidelines such as GxP and 21 CFR Part 11. Staying abreast of the latest advancements in machine learning and artificial intelligence, you will apply industry best practices to address the challenges faced within the clinical supply chain domain. To excel in this role, you should hold a Master's or PhD degree in Computer Science, Data Science, Engineering, or a related field and possess a minimum of 3 years of experience in machine learning, data science, or AI, preferably within healthcare or life sciences. Your practical knowledge of clinical supply chain processes, including demand forecasting, IRT systems, and logistics planning, will be invaluable. Proficiency in programming languages such as Python, R, SQL, and familiarity with ML frameworks like scikit-learn, TensorFlow, and PyTorch are essential. Additionally, your expertise in statistical modeling, time series forecasting, and optimization techniques will be crucial to your success. Effective communication skills and the ability to collaborate across departments in a dynamic environment are essential qualities for this role. Preferred qualifications include experience with clinical trial data (e.g., EDC, CTMS, IRT), knowledge of regulatory requirements in clinical research, and familiarity with cloud platforms such as AWS, Azure, and GCP, along with MLOps practices. Your technical skills in SQL, R, statistical modeling, Python, ML frameworks, time series forecasting, TensorFlow, and your deep understanding of clinical supply chain operations will be instrumental in driving data-driven decision-making and optimizing logistics within our clinical trial supply chain.,

You are a highly analytical and detail-oriented Performance Analytics Specialist being sought to join our team. Your main responsibility will be to design and implement data-driven solutions aimed at monitoring, assessing, and enhancing operational and business performance, particularly within the pharmaceutical industry. A strong foundation in data science, statistical analysis, and business intelligence tools is essential for this role, with a specific focus on aligning with FDA standards and pharmaceutical KPIs. Your key responsibilities will include developing and maintaining performance dashboards using tools such as Power BI, Tableau, and other BI tools. You will analyze operational and business data to identify trends, gaps, and improvement opportunities. Collaboration with cross-functional teams, including MES, QA, and manufacturing, is crucial to align analytics with FDA and pharmaceutical standards. You will design and implement KPI frameworks and performance management indicators, as well as conduct statistical analysis and build predictive models to support decision-making. Ensuring data quality, integrity, and compliance with regulatory standards is paramount, along with automating data processing and reporting workflows using SQL, Python, or R. Your ability to translate complex data into actionable insights for senior management will be essential. Your primary skills should include proficiency in Business Intelligence Tools such as Microsoft Power BI and Tableau, expertise in Data Analysis & Visualization including dashboarding, KPI tracking, and performance metrics, as well as Statistical Analysis proficiency in R, Python, or statistical software. Data Management & Querying skills, including SQL, data processing, and data quality assurance, are also required. Industry Knowledge in Pharmaceutical standards, FDA compliance, and MES systems, as well as experience in Performance Management involving operational KPIs and performance assessment frameworks, will be beneficial. Your secondary skills may involve Programming using Python and R for automation and modeling, Mathematics & Statistics knowledge encompassing applied statistics, regression, and forecasting, as well as Software Development skills for basic scripting in data pipelines. An understanding of Science & Research within pharmaceutical R&D and production environments, familiarity with Technology & IT including relational databases and data warehousing concepts, and effective Communication skills to present insights to technical and non-technical stakeholders will also be advantageous. Preferred qualifications for this role include a Bachelors or Masters degree in Data Science, Statistics, Computer Science, or a related field, experience in the pharmaceutical or healthcare industry, familiarity with MES systems and FDA regulatory frameworks, and certifications in Power BI, Tableau, or other data analytics tools.,

You are looking to hire a mid-level resource with expertise in Artificial Intelligence (AI), Machine Learning, and Deep Learning. As a Machine Learning Engineer, your responsibilities will include studying and transforming data science prototypes, designing machine learning systems, researching and implementing appropriate ML algorithms and tools, developing machine learning applications based on requirements, selecting datasets and data representation methods, running machine learning tests and experiments, performing statistical analysis and fine-tuning using test results, training and retraining systems when necessary, and staying updated on developments in the field. It is essential that you have proven experience in a similar role, an understanding of data structures, data modeling, and software architecture, deep knowledge of math, probability, statistics, and algorithms, the ability to write robust code in Python, Java, and R, familiarity with TensorFlow framework, Keras, PyTorch, Deeplearning4j, and Anaconda, excellent communication skills, the ability to work in a team, and strong analytical and problem-solving skills. If you meet these requirements and are interested in this position, please send your updated resume to recruiter1@pnrsoftsol.com. This job falls under the category of Artificial Intelligence (AI/ML/DL) with a Job ID of AI_ML_DP_KOL. It is a mid-level position in the IT industry, requiring a minimum of 3 years of work experience. The annual CTC is open, and there are 3 vacancies available with a short notice period. The contact person for this job is TAG, and you can reach out to recruiter1@pnrsoftsol.com for further inquiries or to submit your application.,

The Data Scientist is expected to harness large volumes of complex data to generate actionable insights that fuel business strategy and innovation. This role requires expertise in advanced statistical methods, machine learning techniques, and data visualization to discover patterns, forecast outcomes, and support data-driven decision-making across the organization. Transforming complex datasets into solutions is a key aspect of the role, leveraging statistical expertise and machine learning to answer crucial business questions. This includes collecting, cleaning, and preprocessing structured and unstructured data from various sources such as databases, APIs, logs, and documents. Investigating data sets to identify patterns, anomalies, trends, and correlations through Exploratory Data Analysis (EDA) is essential for informing hypotheses and model development. Designing, implementing, and fine-tuning statistical and machine learning models for prediction, classification, segmentation, and recommendation tasks is a core responsibility. Evaluating model performance using appropriate metrics and iterating to improve robustness and generalizability is crucial. Translating complex model outputs into intuitive visualizations and business-relevant narratives using tools like Power BI, Tableau, or custom dashboards is important for effective data storytelling and visualization. Presenting findings and actionable recommendations to stakeholders in a clear and compelling manner to enable informed decision-making across departments is a key part of the role. Collaborating closely with business, product, engineering, and operations teams to understand domain-specific challenges and deliver tailored data-driven solutions is essential. Staying updated on the latest developments in data science, AI/ML frameworks, and big data technologies to incorporate cutting-edge methods into workflows is also a required aspect. The ideal candidate should possess deep proficiency in Python or R, along with fluency in SQL and familiarity with core data manipulation libraries such as NumPy, Pandas, and Scikit-learn. The ability to translate complex data outputs into clear, concise, and visually compelling insights for technical and non-technical stakeholders is necessary. A solid grasp of business fundamentals to connect analytical findings with strategic decision-making is crucial, along with having a naturally analytical mindset and a passion for uncovering insights, solving problems, and discovering meaningful patterns within data. Educational qualifications for this role include an advanced degree (Masters or PhD) in a quantitative discipline such as Statistics, Mathematics, Computer Science, or a closely related field. The ideal candidate should have 3+ years of demonstrated experience in data science, showcasing a strong command of statistical modeling and machine learning techniques. The Data Scientist role falls under the Software Division and reports to the CTO Org.,