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Tier-1 brand, popular data scientist title, mid-level experience, and metro location create high competition.
Strong ML/GenAI skills transfer across industries, but financial-services domain preference raises sensitivity.
Explicit 3+ years requirement plus mandatory ML/GenAI, production and tooling experience increases filtering.
Perform multiple analyses on business problems to improve client experience, acquisitions, cross-sell and revenue growth in Treasury & Trade Services business.
Leverage multiple analytical approaches and data sources (structured/unstructured) including emails, call transcripts, transactions, to provide actionable insights.
Design, implement and scale production-grade Generative AI applications including Gen AI projects with data analysis, prompt tuning, RAG, and Agentic RAG techniques.
Bachelor’s degree with 3+ years or Master’s degree with 2+ years experience in analytics.
Experience in financial services industry solving business problems related to sales/marketing strategy optimization, pricing, client experience, cross-sell, or retention.
Proficiency in Python/R, PySpark, data manipulation including unstructured data from big data environments.
Experience with ML, DL, and Generative AI techniques including RAG, prompt engineering, fine tuning.
Experienced in translating ambiguous, cross-functional business problems into analytical frameworks and delivered capabilities.
Operates with a working knowledge of industry practices and integrates disciplinary expertise within analytics and AI/ML.
Comfortable collaborating across product, business, operations, and data teams to prioritize and solve problems involving large, complex, multi-source datasets.