Senior Data Scientist

Mastercard
Gurgaon, IndiaPosted 6 April 2026

Job Description

Our Purpose Mastercard powers economies and empowers people in 200 countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Data Scientist Senior Data Scientist, Product Data & Analytics Our Vision: Product Data & Analytics team builds internal analytic partnerships, strengthening focus on the health of the business, portfolio and revenue optimization opportunities, initiative tracking, new product development and Go-To Market strategies. We are a hands-on global team providing scalable end-to-end data solutions by working closely with the business. We influence decisions across Mastercard through data driven insights. We are a team on analytics engineers, data architects, BI developers, data analysts and data scientists, and fully manage our own data assets and solutions. • Are you excited about Data Assets and the value they bring to an organization? • Are you an evangelist for data driven decision making? • Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across the continents? • Are you interested in proactively looking to improve data driven decisions for a global corporation? Role • Responsible for developing data-driven innovative scalable analytical solutions and identifying opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations / decisions. • Accountable for delivering high quality project solutions and tools within agreed upon timelines and budget parameters and conducting post- implementation reviews. • Contributes to the development of custom analyses and solutions, derives insights from extracted data to solve critical business questions. • Activities include developing and creating predictive models, behavioural segmentation frameworks, profitability analyses, ad hoc reporting, and data visualizations. • Work closely with global & regional teams to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support analytics and reporting needs across products, markets, and services. Support initiatives in developing predictive models, behavioural segmentation frameworks, profitability analyses, ad hoc reporting, and data visualizations. • Able to develop AI/ML capabilities, as needed on large volumes of data to support analytics and reporting needs across products, markets and services. • Able to build end to end reusable, multi-purpose AI models to drive automated insights and recommendations. • Leverage open and closed source technologies to solve business problems. • Translates client/ stakeholder needs into technical analyses and/or custom solutions in collaboration with internal and external partners, derive insights and present findings and outcomes to clients/stakeholders to solve critical business questions. • Create repeatable processes to support development of modelling and reporting • Delegate and reviews work for junior level colleagues to ensure downstream applications and tools are not compromised or delayed. • Serves as a mentor for junior-level colleagues, and develops talent via ongoing technical training, peer review etc. All About You • 7-9 years of experience in data management, data mining, data analytics, data reporting, data product development and quantitative analysis. • Advanced SQL skills, ability to write optimized queries for large data sets. • Experience on Platforms/Environments: Cloudera Hadoop, Big data technology stack (Hadoop, hive, spark), SQL Server, Microsoft BI Stack, Clou ... (truncated, view full listing at source)
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