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Nikita Vivek Kolhe
Junior Data & Machine Learning Engineer specializing in MLOps and NLP
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ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).
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Key Strengths
- Built and deployed LLM-powered sentiment analysis pipeline for healthcare reviews (RateMDs) with RAG for review querying
- Improved sentiment classification performance by addressing class imbalance with SMOTE
- Designed interpretable, non-technical-user-friendly dashboards to communicate model outputs
- Led optimization of Nike Fusion ETL pipeline using orchestration/DAGs; improved runtime efficiency by 20%
- Strong ML workflow rigor: modular design, unit tests, cross-validation/holdout evaluation, metric-driven iteration with end-user feedback
- Effective collaboration with non-technical stakeholders; delivered Tableau dashboard for 30-day hospital readmission prediction insights
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