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Kavya Paluvai
Mid-level Data Scientist specializing in fraud detection and healthcare ML
North Carolina, USAData Analyst4 years experienceMid-LevelFinancial ServicesBankingHealthcare
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About
Applied NLP/ML in healthcare and financial services, including fine-tuning BERT on unstructured EHR text and building embedding-based similarity search for clinical concepts. Also redesigned a Wells Fargo fraud detection data pipeline using modular Python + AWS Glue/Step Functions, cutting runtime ~40% with improved monitoring and reliability.
Experience
Data AnalystWells Fargo
Principal Data AnalystNextGen Healthcare
Education
University of North Carolina Charlottemaster, Data Science and Business Analytics (2024)
Key Strengths
- Improved clinical text classification accuracy ~20% by fine-tuning BERT on EHR data
- Built domain-specific preprocessing/tokenization (custom vocab, abbreviation standardization, dataset balancing) to reduce noise and boost model performance
- Entity resolution across patient/provider systems using fuzzy matching + manual validation/tuning
- Improved semantic linking/search relevance ~25% via domain fine-tuned embeddings (e.g., linking 'heart attack' and 'myocardial infarction')
- Designed production-grade Python data workflows with Airflow + AWS Glue, logging/monitoring in CloudWatch, and Git versioning
- Reduced fraud detection pipeline runtime ~40% at Wells Fargo by modularizing AWS Glue workflow, enabling parallel tasks and reusable components
- Moved models from notebook experimentation to production using AWS SageMaker pipelines with reproducible tracking/versioning
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