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Tier-1 brand, popular mid-level data scientist role in metro with broad skill requirements.
Core data science skills are transferable, but payments and pricing experience preference raises domain sensitivity to medium.
Explicit 5+ years and extensive mandatory tech stack and domain skills indicate high shortlisting strictness.
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Design and deliver advanced analytics and machine learning models to support Mastercard's Global Pricing & Interchange strategy and revenue optimization.
Develop, maintain, and scale data pipelines, dashboards, and data products using modern cloud and big data technologies to support enterprise decision-making.
Collaborate with cross-functional teams and present insights to senior leadership to influence strategic commercial decisions and mentor junior analysts.
5+ years of experience in data science, advanced analytics, or quantitative modeling.
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or related field required.
Proficiency in advanced SQL, Python programming, and experience with big data technologies such as Spark, Hive, Hadoop, Snowflake, or Databricks.
Experience with data visualization tools (Power BI, Tableau) and cloud platforms (Azure, AWS) with knowledge of machine learning model development and deployment.
Strong expertise in building scalable data pipelines and predictive analytics solutions in large-scale, complex data environments.
Able to translate complex quantitative analyses into actionable business insights influencing pricing and commercial strategy decisions.
Experienced in working cross-functionally with strategy, finance, product, and technology teams in fintech, payments, or financial services domains.