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Divya Ganapala
Mid-level Data Scientist specializing in cloud ML, MLOps, and predictive analytics
UnitedHealth GroupJawaharlal Nehru Technological University, HyderabadDallas, TX4 Years ExperienceMid Level
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About
NLP/ML engineer with hands-on healthcare and support-ticket text experience, building clinical-note structuring and semantic linking systems using spaCy, BERT clinical embeddings, and FAISS. Emphasizes production-grade delivery (Airflow/Databricks, PySpark, Docker, AWS/FastAPI/Lambda) and rigorous validation via clinician-labeled datasets, retrieval metrics, and user feedback.
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Built NLP pipeline to structure clinical notes using spaCy + BERT clinical embeddings
Designed relationship-mapping layer combining embeddings, structured clinical features (ICD/med classes/time windows), and clinician-labeled validation
Hybrid entity resolution approach (deterministic + probabilistic + embedding similarity) with precision/recall/pairwise F1 evaluation
Improved semantic search/data linking using FAISS vector index and domain fine-tuning; measured gains with offline metrics and user feedback
Production-grade Python workflow engineering (modular design, orchestration with Airflow/Databricks, distributed processing with PySpark, containerized AWS deployments)
Clear prototype-to-production process using retrieval metrics (precision, MRR), stability checks, and stakeholder alignment
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Experience
Data ScientistUnitedHealth Group · Jun 2024 – Present
Data ScientistStridez Solutions · Jun 2022 – Jul 2023
Data ScientistRamTech · Jul 2021 – Jun 2022
Education
Jawaharlal Nehru Technological University, Hyderabadbachelor, Information Technologies
University of North Texasmaster, Data engineering in computer science
Mid-level AI/ML Engineer specializing in NLP, RAG, and MLOps
McKinney, TX6y exp
Globe LifeTexas A&M University
“Built a production LLM/RAG-based “model excellence scoring” system at Uber to automatically evaluate hundreds of ML models, standardizing quality assessment and cutting evaluation time from days to minutes on GCP. Also delivered an NLP document classification solution for insurance claims at Globe Life, partnering closely with compliance/operations and improving routing accuracy from ~85% manual to 93% with the model.”