Sathwik Vuppala
@sathwikvuppala
I build production machine learning systems for risk, fraud, and healthcare analytics.
United StatesWhat I'm looking for
At JPMorgan Chase, I build NLP-based KYC intelligence that classifies documents and extracts client information across more than 1 million annual documents. I also develop entity-resolution, risk-prioritization, and retrieval workflows that improve accuracy, traceability, and onboarding review.
Previously at Accenture, I built health-insurance claims triage and fraud-detection models across 10 million-plus claims. I take models from Python, SQL, and PySpark feature engineering through AWS deployment, evaluation, explainability, and drift monitoring.
Experience
Work history, roles, and key accomplishments
Developed NLP-based KYC document intelligence and entity-resolution models, improving classification accuracy by 18% and matching accuracy by 15%. Productionized models on AWS with SageMaker, MLflow, Airflow, and Docker, implementing automated scoring and drift monitoring.
Architected health-insurance claims intelligence and fraud-detection models, improving triage accuracy by 16% and reducing false-positive investigations by 14%. Productionized models on AWS using SageMaker, S3, Docker, MLflow, and Airflow.
Education
Degrees, certifications, and relevant coursework
George Mason University
Master of Science, Computer Science Engineering
Master of Science in Computer Science Engineering from George Mason University.
Availability
Location
United StatesAuthorized to work in
Salary expectations
Skills
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