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GenAI popularity and broad experience band increase applicants but niche Agentic AI skills moderate competition.
Core GenAI/ML skills are transferable but insurance analytics and Agentic AI domain knowledge raise specificity.
Multiple mandatory GenAI, LLM, and tooling skills required but broad experience range keeps filters moderate.
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Lead design and deployment of autonomous AI solutions improving business workflows like claims processing, underwriting, and customer servicing.
Collaborate closely with clients and internal teams to identify new AI opportunities and establish trusted advisor relationships.
Analyze structured and unstructured data to diagnose inefficiencies and drive issue resolution across functional areas.
Bachelor's or Master's degree in economics, mathematics, computer science/engineering, operations research, or related analytics field; top-tier institution graduates with BA/BS also considered.
2-10 years of professional experience in AI, Generative AI, or Machine Learning.
Hands-on experience with GenAI tools such as AWS, Python, Langchain, Langgraph, VectorDB, and knowledge of segmentation, advanced analytics, ML, statistical, data mining, NLP techniques, and Agentic AI frameworks (including Crew AI exposure).
Experience or exposure to insurance analytics is mandatory.
Proven ability to work as an individual contributor with clients globally in fast-paced, evolving environments requiring cross-cultural communication.
Strong analytical problem-solver with a track record of achievement and entrepreneurial approach to AI solution building.
Experienced in building long-term client relationships and managing stakeholder engagements to identify growth opportunities in AI-driven analytics.