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Ugochukwu Obunadike
Principal Data Scientist specializing in Generative AI, NLP, and MLOps
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About
ML/NLP practitioner with banking experience (M&T Bank) who has built a GPT-4 RAG system using LangChain and Pinecone to connect unstructured customer data with internal knowledge bases, improving accuracy and reducing manual lookup time by 50%+. Strong in entity resolution and productionizing scalable Python data workflows, including major performance wins by migrating bottleneck joins from Pandas to Dask.
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Key Strengths
- Built production RAG system connecting unstructured customer data to internal knowledge bases
- Tooling/architecture selection for scalable vector search (LangChain + Pinecone + GPT-4)
- Entity resolution expertise (fuzzy matching, TF-IDF similarity, clustering) with rigorous validation
- Improved response accuracy and cut manual data lookup time by 50%+
- Performance optimization of data workflows (Pandas to Dask) reducing runtime from 1+ hour to <10 minutes
- Production-grade Python workflow practices (modular design, testing, logging, documentation, scalability)
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