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Specialized GenAI skillset but broad experience band and popular Data Scientist title increases applicant competition.
Core GenAI and LLM skills are transferable, but insurance analytics preference raises domain specificity.
Explicit 2–10 years requirement plus mandatory GenAI tooling and insurance exposure enforces moderate filtering.
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Drive design and deployment of GenAI and Agentic AI autonomous solutions to improve business workflows including claims processing, underwriting, customer servicing, and decision automation.
Collaborate closely with client and internal teams to establish stakeholder relationships, identify growth opportunities, and ensure adherence to industry best practices.
Analyze structured and unstructured data to diagnose process inefficiencies and lead client sessions and status meetings as an individual contributor.
Bachelor’s/Master's degree in economics, mathematics, computer science/engineering, operations research, or related analytics areas from top-tier institutions also acceptable.
2-10 years of work experience specifically in AI, Generative AI (GenAI), and Machine Learning.
Hands-on experience with GenAI tools such as AWS, Python, Langchain, Langgraph, VectorDB, and knowledge of segmentation, advanced analytics, machine learning, statistical/data mining, NLP techniques, and Agentic AI frameworks; exposure to Crew AI is a plus.
Experience or exposure to insurance analytics domain.
Experienced data scientist or AI practitioner with strong expertise in GenAI/Agentic AI systems and production-grade AI solution development.
Ability to build trusted advisor relationships with clients and identify opportunities for AI-driven process improvements.
Comfortable working independently with diverse global stakeholders and in fast-paced, evolving environments requiring problem diagnosis and resolution.