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Mid-level Data Scientist in a metro with broad ML/GenAI requirements increases applicant competition.
Strong Banking/Financial Services preference and specialized GenAI skills limit cross-industry transferability.
Mandatory 5+ years plus specific ML/GenAI, SageMaker and Bedrock experience creates strict filters.
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Lead end-to-end AI/ML projects from ideation through deployment and stakeholder handover in the Banking and Financial Services domain.
Develop scalable machine learning solutions using Python, AWS SageMaker, Dataiku, and AWS Bedrock aligned with business objectives across Marketing, Operations, and Digital Banking.
Mentor and guide junior data scientists and ML engineers while managing multiple AI/ML initiatives and delivering GenAI solutions using modern LLM models.
Minimum 5+ years of experience in Data Science and AI, preferably in Banking and Financial Services.
Strong expertise in supervised and unsupervised ML, classification, data/text mining, NLP, decision trees, random forests, model explainability, and ML model deployment.
Hands-on experience with Python, AWS SageMaker, Dataiku; experience with AWS Bedrock and LLM models mandatory for GenAI solutions.
Work location expectation: Minimum 3 days per week in-office (Pune, MH). Notice period: Not explicitly mentioned in the JD.
Proven ability to translate complex business challenges into actionable AI/ML solutions partnering with cross-functional teams.
Experienced in managing multiple concurrent AI/ML projects with timely delivery and effective stakeholder communication.
Technical leadership capability with experience mentoring junior data scientists and driving collaborative environments focused on enterprise decision-making.