Senior Specialist, Strategy Pricing & Interchange

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 Specialist, Strategy Pricing & Interchange Role Overview Mastercard is seeking a highly analytical and commercially minded professional to join the RAISE Value Quantification team within Strategy Pricing & Interchange. This role will help shape how Mastercard translates product, service, and customer value into scalable pricing strategies, business cases, and decision-ready analytics. The ideal candidate will bring strong experience in predictive modeling, machine learning, pricing analytics, and data science, combined with the ability to influence commercial decisions. The role partners closely with Product, Pricing, Commercialization, Data Science, and regional teams to build value-based pricing models, quantify customer impact, and support growth-oriented pricing decisions across Mastercard. ________________________________________ Key Responsibilities 1. Predictive Modeling and Explainability a. Design and build predictive models that quantify the economic, operational, and customer value of Mastercard products and services. b. Measure revenue, cost savings, efficiency, risk reduction, and customer impact to inform pricing and commercialization decisions. c. Translate model outputs into clear value stories, commercial insights, and business cases. 2. Pricing Analytics & Modeling a. Develop value-based B2B pricing models, commercial frameworks, and analytical tools that support product pricing and go-to-market strategy. b. Estimate adoption, revenue impact, customer economics, churn elasticity, and outcome-based scenarios. c. Run pricing scenarios and sensitivity analyses to guide strategic trade-offs and executive decision-making. 3. Machine Learning & Advanced Analytics a. Apply machine learning, statistical techniques, and advanced analytics to identify pricing opportunities, customer value drivers, and performance trends. b. Analyze large datasets and prepare structured inputs for predictive modeling. c. Build forecasts and analytical outputs that support pricing strategy, product planning, and performance management. ________________________________________ Qualifications Education • Master's degree in quantitative fields such as Data Science, Statistics, Economics, Engineering, Finance, Mathematics, Computer Science, or Operations Research. Must-Have Experience