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Strong Tier-1 brand, mid-level generalist title, broad skillset, and 5+ years experience create high applicant competition.
Core data science skills are transferable, but payments/pricing preference adds domain bias, so medium sensitivity.
Explicit 5+ years requirement plus many mandatory technologies and domain preferences makes shortlisting highly strict.
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Design and deliver advanced analytics, predictive models, and scalable data science solutions to support Mastercard’s Pricing & Interchange strategy and business performance optimization.
Develop and maintain data pipelines, dashboards, and data products using modern cloud and big data technologies for global business needs.
Collaborate with cross-functional teams to generate actionable insights influencing strategic commercial decisions and present findings to senior leadership.
5+ years of professional experience in data science, advanced analytics, quantitative modeling, or related disciplines.
Strong skills in SQL, Python, and experience with big data technologies such as Spark, Hive, Scala, and cloud platforms like Azure/AWS.
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or related field.
Proficiency in data visualization tools (Power BI/Tableau) and experience building/maintaining data pipelines and transformation frameworks (Databricks, Alteryx, SSIS).
Experienced in payments, financial services, fintech, pricing, or commercial analytics domain preferred.
Skilled in applying machine learning, AI-driven approaches, and optimization models to solve complex business challenges.
Capable of translating complex data analyses into clear business insights and recommendations, with experience mentoring junior data scientists.