Data Scientist II, Product Data & Analytics

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 Data Scientist II, Product Data & Analytics Data Scientist II, Product Data & Analytics Our Vision The Product Data & Analytics team builds internal analytics partnerships that strengthen focus on business health, portfolio performance, revenue optimization, initiative tracking, new product development, and go-to-market strategies. We are a hands-on global team that delivers scalable, end-to-end data solutions in close partnership with the business. Through data-driven insights, we influence decisions across Mastercard. Our team includes analytics engineers, data architects, BI developers, data analysts, and data scientists who collectively manage our data assets and analytical solutions. What We Look For • Are you excited by the value that data assets can bring to an organization? • Are you an advocate for data-driven decision-making? • Are you motivated to be part of a global analytics team that builds large-scale analytical capabilities for users across continents? • Are you interested in proactively improving data-driven decisions for a global corporation? Role Responsibilities • Partner with global and regional teams to design, develop, and maintain advanced reporting and data visualization capabilities using large-scale data sets across products, markets, and services. • Translate business requirements into clear solution specifications and deliver high-quality outputs on time. • Create repeatable processes for ETL development, data modelling, and reporting. • Use analytical tools to manipulate large-scale databases, synthesize insights, and present findings through Tableau, Power BI, Excel, and PowerPoint. • Apply quality control, data validation, and cleansing processes to both new and existing data sources. • Bring passion, curiosity, and technical expertise to every engagement. Candidate Profile • 3–5 years of experience in data engineering and management, data mining, data analytics, reporting, data product development, or quantitative analysis. • Advanced SQL skills, including the ability to write optimized queries for large data sets. • Experience writing stored procedures, functions, and views is preferred. • Experience with platforms and environments such as Databricks, Cloudera Hadoop, big data technology stacks, SQL Server, Microsoft BI Stack, cloud platforms, Snowflake, and related technologies. • Exposure to Python, Scala, Hive, Impala, Spark, cloud technologies, and related tools.