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Tier-1 brand, mid-level ML title, Pune metro, hybrid work and broad skills increase candidate competition.
Fraud and financial-services experience preferred, but core ML and data skills are broadly transferable across industries.
Explicit 4–8 year requirement, advanced degree, and mandatory ML, Python, SQL and deployment skills enforce high strictness.
Analyze large, complex datasets to identify fraud patterns and inconsistencies using advanced analytics and machine learning.
Build, validate, optimize, and enhance machine learning models focused on fraud detection and prevention at enterprise scale.
Collaborate with cross-functional teams to deliver scalable analytical solutions and effectively communicate insights to both technical and non-technical stakeholders.
4 to 8 years of relevant Data Science experience.
Advanced degree in Statistics, Mathematics, Computer Science, Engineering, or related fields.
Strong programming skills in Python (3.7+) and proficiency in SQL and Excel.
Experience with machine learning techniques (clustering, decision trees, boosting), model deployment, and familiarity with cloud platforms such as AWS or Azure.
Experienced in applying machine learning and statistical techniques specifically for fraud analytics or financial crime detection.
Able to operate proficiently in agile, multi-disciplinary teams with an emphasis on delivering high-quality, scalable analytical solutions.
Skilled at translating complex analytical concepts into clear communication for diverse stakeholder groups, including business and engineering teams.