[ ABOUT ME ]

Health informatics and applied AI, from research to production

I'm Jay Nagabhairu, a Data Scientist with a health informatics background and hands-on experience building production large language model and retrieval-augmented generation systems for healthcare. My work spans electronic health record and claims data, natural language processing, and applied machine learning — always with an eye toward what makes a tool genuinely usable, not just technically impressive.

I've built conversational AI tools, document-intelligence systems using OCR, and computer vision applications inside complex, highly regulated healthcare data environments. That work taught me to build systems that are not just accurate, but auditable, explainable, and trustworthy — which matters enormously in healthcare.

I hold an MS in Health Informatics and Data Science from Georgetown University, completed with a 4.0 GPA. I'm currently exploring opportunities where I can bring this combination of technical depth and health domain expertise to a product-focused team.

Jay Nagabhairu at the AWS Summit in Washington, DC
Jay Nagabhairu at the ODSC AI conference
Work_History

  1. Booz Allen Hamilton

    Oct 2025 — Present

    Data Scientist II & Senior Consultant

    • •Design and maintain production RAG and LLM pipelines powering conversational AI tools used in healthcare contexts.
    • •Build ML solutions on electronic health record and medical claims data — data cleaning, feature engineering, and model development.
    • •Develop OCR-based document intelligence and computer vision systems that turn unstructured healthcare documents into structured data.
    • •Work across the full data science lifecycle inside highly regulated environments, with close attention to governance, privacy, and security.

  2. ICA AI

    Jun 2025 — Present

    AWS Health Data Intern

    • •Developed scalable AWS pipelines using S3, Glue, and DynamoDB to process mental health and SDOH datasets.
    • •Built ML/NLP features with SageMaker and Bedrock, and designed dashboards with QuickSight and Streamlit.

  3. Knope

    Sep — Dec 2024

    Graduate Data Science Intern

    • •Built a TensorFlow computer vision model to interpret drug test results with 92% accuracy.
    • •Developed a geolocation-based analytics tool to detect drug-assisted assault hotspots.

  4. Care AI

    Feb — Jul 2023

    AI/ML Engineering Intern

    • •Improved a CNN model for fall detection, deployed across 200+ medical sensors with 92% accuracy and 0.86 F1-score.
    • •Built a Streamlit dashboard for real-time device monitoring used by 50+ engineers.

  5. Andor Health

    2020 — 2021

    Product & BI Intern (2 Roles)

    • •Led R&D for a generative AI discharge planning assistant; filed 5 utility patents.
    • •Created Azure-based Power BI pipelines and aggregated 30,000+ data blocks into dashboards.
Education

Georgetown University

MS in Health Informatics & Data Science · 4.0 GPA

University of Central Florida

BS in Data Science

By_The_Numbers
Years Building0+
ML Models Shipped0+
Records Powered0M+