Gen AI

"Role Objective: To design and deploy high-impact ML and Generative AI solutions that transform unstructured insurance data into actionable insights for the P&C value chain.

Key Responsibilities:

Predictive Modeling: Build and refine P&C-specific models: Claims Severity, Litigation Propensity, and Fraud Scoring.

Generative AI & NLP: Develop RAG (Retrieval-Augmented Generation) and Agentic AI workflows using Claude (Bedrock) and Azure OpenAI to automate claim summaries.

Unstructured Data Intelligence: Engineer semantic extraction tools to process adjuster notes and policy files into curated Delta Tables.

Decision Systems: Implement Agentic AI and Graph-based networks (Neo4j) for automated claim-to-adjuster assignment and similarity matching.

Tech Stack: Python, PySpark, LangChain, LlamaIndex, spaCy, AWS Bedrock."