Develops production-grade data and analytics solutions, applies statistics and machine learning to business problems, and mentors data scientists. Responsibilities include feature engineering, modeling, NLP, generative AI, MLOps, cloud AI services, stakeholder engagement, analytical storytelling, and structured problem solving within the banking, financial services, and insurance domain.

Design, build, and operate production AI services, agentic workflows, and LLM-powered features. Responsibilities include developing Python APIs and microservices, implementing RAG and vector search, optimizing model inference, integrating event-driven systems, deploying services on Docker and Kubernetes, monitoring reliability, managing CI/CD and testing, and partnering with frontend teams to deliver end-to-end AI products.

Develops production-grade data science and analytics solutions across broad business problems. Responsibilities include statistical analysis, hypothesis testing, feature engineering, machine learning modeling, NLP, OCR, generative AI, prompt engineering, and MLOps using cloud AI services. The role mentors data scientists, partners with stakeholders, communicates insights through storytelling, and applies expertise to banking, financial services, and insurance use cases.