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Popular mid-range Data Scientist role with broad GenAI/ML requirements increases competition.
Core ML/GenAI skills are transferable, but insurance consulting experience increases domain specificity.
Explicit years plus required GenAI/ML tools and domain experience make screening strict.
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Design and deploy intelligent autonomous solutions to improve business workflows like claims processing, underwriting, and decision automation.
Collaborate closely with clients and internal teams to identify opportunities, establish stakeholder relationships, and lead project status meetings.
Analyze structured and unstructured data to diagnose inefficiencies and deliver scalable, production-grade GenAI/Agentic AI solutions.
Bachelor's or Master's degree in economics, mathematics, computer science/engineering, operations research, or related analytics fields; top tier institutions preferred.
2-10 years of work experience in AI, Generative AI, or Machine Learning.
Hands-on experience with GenAI tools (AWS, Python, Langchain, Langgraph, VectorDB) and knowledge of Agentic AI frameworks including Crew AI.
Exposure to insurance analytics domain.
Experienced in managing client relationships and working cross-culturally with global clients as an individual contributor.
Strong foundational skills in data science coupled with practical expertise in LLMs, prompt engineering, Agentic AI orchestration frameworks, and advanced analytics.
Analytical, problem-focused approach with a proven track record of delivering impactful AI solutions in fast-paced, evolving environments.