Data Science | Building Agentic RAG Systems & LLM Applications with LangChain, LangGraph & Python
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Aspiring Data Scientist (CDAC 2026) specializing in production-grade agentic AI systems. Engineered a LangGraph-based RAG Data Analyst with ChromaDB retrieval, BGE reranking, and dual self-correction loops — achieving 92% SQL accuracy and 0.91 RAGAS faithfulness. Across 5 end-to-end projects, delivered 71% agent self-recovery, 93% query turnaround reduction, 99% faster insight generation on 393K+ reviews, and 91% ML pipeline precision on 500K+ records via PySpark.
Proficient in LangChain, LangGraph, OpenAI API, Hugging Face, ChromaDB, BERT, XGBoost, FastAPI, and Streamlit — from prompt engineering to CI/CD-gated deployment.
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