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Rohan Chodapunedi
Entry-level Data Scientist specializing in LLMs and analytics
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About
Built a zero-to-one AI contract/policy QA agent for compliance and data teams, with a strong emphasis on trust, traceability, and clause-level citations rather than just fluent answers. They combine full-stack product ownership with practical LLM systems design, including hybrid retrieval, structured outputs, and evaluation pipelines to improve reliability, latency, and cost.
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Key Strengths
- Built and shipped a production contract/policy QA agent for real internal users
- Strong retrieval architecture design for high-trust document QA
- Deep focus on grounded, auditable AI outputs with clause-level citations
- End-to-end ownership across React frontend and FastAPI/backend services
- Pragmatic optimization of accuracy vs latency tradeoffs
- Robust evaluation mindset using QA benchmarks and LLM-as-judge
- Iterative product development driven by direct user feedback
- Good failure handling design with uncertainty surfacing and insufficient-info thresholds
- Zero-to-one scoping in ambiguous environments
- Domain fluency in legal, policy, compliance, and data-team workflows
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