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Tier-1 brand, metro location, and popular mid-level data scientist role create high candidate competition.
ML and production data skills transferable, but payments and product domain expertise increases fit sensitivity.
Requires hands-on ML, Spark/Hadoop, production model, and pipeline experience, so moderately strict technical filters.
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Design, develop, deploy, and maintain advanced machine learning and data science solutions that optimize Mastercard's digital payment products and drive business impact.
Lead end-to-end technical oversight of complex ML models including development, validation, monitoring, and continuous improvement aligned with business objectives.
Create scalable data pipelines and translate analytical insights into actionable recommendations for senior business and product stakeholders.
Strong academic background in Computer Science, Data Science, Technology, Mathematics, Statistics, or related fields, or equivalent work experience.
Proficiency in Python, SQL, and big data platforms such as Spark and Hadoop (Hive, Impala, Airflow, NiFi).
Experience with machine learning frameworks, statistical techniques, model evaluation, and performance monitoring.
Work Experience Required: Not explicitly mentioned in the JD.
Experience working cross-functionally with global teams to drive product optimization and growth through data science solutions.
Demonstrated ability to lead design and technical oversight of scalable ML solutions in fast-paced, deadline-driven environments.
Skilled at translating complex model results into clear business insights and managing data pipelines involving large-scale, high-dimensional datasets.