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Popular GenAI/data scientist role with mid-level experience range and broad, in-demand LLM skills.
GenAI and LLM skills are transferable, though insurance analytics and client-facing consulting add moderate industry specificity.
Explicit 2–10 year requirement plus mandatory GenAI, LLM and tool experience increases filter strictness.
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Drive the design and deployment of intelligent, autonomous AI solutions to improve business workflows in areas like claims processing, underwriting, and customer servicing.
Collaborate closely with client and internal teams to identify new opportunities and establish trusted advisor relationships with stakeholders.
Analyze structured and unstructured data to diagnose process inefficiencies and lead resolution initiatives while facilitating client sessions and project meetings.
Bachelor's or Master's degree in economics, mathematics, computer science/engineering, operations research or related analytics fields; degrees from top tier institutions preferred.
2-10 years of experience in AI, Generative AI, or Machine Learning.
Hands-on experience with GenAI tools including AWS, Python, Langchain, Langgraph, VectorDB, and familiarity with segmentation, advanced analytics, machine learning, statistical techniques, data mining, NLP, and Agentic AI frameworks such as Crew AI.
Exposure to insurance analytics is required.
Experienced in building scalable, production-grade AI solutions with a strong foundation in data science fundamentals and AI orchestration frameworks.
Capable of working individually with stakeholders in fast-paced, evolving environments across global, cross-cultural clients.
Demonstrates strong critical thinking, problem-solving skills, and a proven track record of analytical achievement and client-facing consulting experience.