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Known analytics employer, mid-level GenAI role, and broad AI skillset increase competition.
Core ML/GenAI skills are transferable, but insurance domain preference increases specificity.
Explicit 2–10 years plus mandatory GenAI, LLM and tooling requirements make filters strict.
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Drive design and deployment of intelligent autonomous AI solutions to improve business workflows such as claims processing, underwriting, customer servicing, and decision automation.
Collaborate closely with client and internal teams to establish stakeholder relationships, identify growth opportunities, and lead recurring project status meetings.
Analyze structured and unstructured data to diagnose process inefficiencies and develop AI-driven resolutions, serving primarily as an individual contributor with client-facing responsibilities.
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 experience in AI, Generative AI, and Machine Learning.
Hands-on experience with GenAI tools such as AWS, Python, Langchain, Langgraph, VectorDB; good knowledge in segmentation, advanced analytics, ML, statistical/data mining, NLP techniques, and Agentic AI frameworks (including Crew AI exposure).
Experience with insurance analytics.
Experienced data scientist combining strong data science fundamentals with practical GenAI and Agentic AI skills to build scalable production-grade AI solutions.
Comfortable working directly with global clients and internal teams in fast-paced, evolving environments, diagnosing complex business problems and delivering actionable AI solutions.
Proven ability to establish trusted advisor relationships with stakeholders and drive business growth opportunities through analytics and AI innovation.