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Harsh Patel
Senior Data Scientist specializing in LLM applications, RAG systems, and production ML
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About
Senior Data Scientist in consulting who has built production RAG systems for insurance/annuity document search at large scale (100K+ PDF pages), emphasizing grounded answers, guardrails, and low-latency retrieval. Experienced in end-to-end MLOps for LLM apps—monitoring, evaluation sets, drift handling, and safe rollouts—and in orchestrating complex pipelines with Prefect/Airflow and deploying services on Kubernetes.
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Key Strengths
- Built and deployed end-to-end RAG system over 100K+ pages of annuity PDFs
- Strong focus on retrieval accuracy, hallucination reduction, and low-latency performance at scale
- Production reliability practices: monitoring, logging, fixed eval sets, regression checks, and controlled rollouts
- Designs AI workflows as debuggable stages with clear metrics and multi-layer testing (offline eval, unit/integration, load/latency)
- Hands-on orchestration of complex ML/data workflows using Prefect (task dependencies, retries, monitoring UI)
- Effective collaboration with non-technical stakeholders via iterative demos and feedback-driven refinement
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