Senior AI/ML Engineer at JPMorgan Chase

Led the end-to-end development and deployment of fraud-detection ML solutions in a regulated banking environment. Designed and productionized models using Amazon SageMaker, PyTorch, and TensorFlow within a microservices architecture, delivering real-time predictions to customer-facing applications via AWS API Gateway and Step Functions. Built a centralized feature store, implemented model explainability with SHAP/LIME, and automated monitoring with CloudWatch to detect drift. Achieved a 35% improvement in transaction security. Mentored junior engineers and conducted GenAI workshops; piloted RAG-based NLP models for investment analysis; supported regulatory compliance and secure data governance.

AI/ML Engineer at AMGEN Inc

Designed and implemented ML pipelines automating predictive modeling for patient diagnostics and treatment personalization. Developed deep learning models with TensorFlow and PyTorch on AWS in HIPAA-compliant environments; applied NLP to extract clinical insights from unstructured texts; built data ingestion via AWS Glue and Athena; established CI/CD pipelines with CodePipeline and Docker. Implemented real-time anomaly detection in billing workflows; evaluated models with ROC-AUC and F1-score; visualized results with Tableau/QuickSight; integrated GenAI models into healthcare analytics workflows and ensured HIPAA/HITECH compliance.

Senior Data Scientist at Safety Insurance Group, Inc.

Designed and deployed predictive models for policyholder risk, claims processing, and underwriting efficiency using Azure ML; managed data using Azure Data Lake and Azure SQL; built fraud-detection models; developed pricing models using Azure Databricks; applied NLP to customer service records; migrated on-prem models to Azure cloud; delivered dashboards with Power BI and Azure Synapse; applied deep learning to claims image analysis; enforced data governance with Azure Purview; performed time-series forecasting for lapse rates and retention; mentored junior data scientists in Azure ML Ops and governance.

Data Scientist at Dell Technologies Inc

Designed end-to-end data pipelines using Azure Data Factory; built predictive analytics models with Azure ML Studio; created real-time dashboards with Power BI; applied NLP to unstructured customer feedback; deployed cloud-based ETL frameworks on Azure; used HDInsight for big data analytics; developed recommendation systems; performed time-series forecasting for sales; automated model deployment via Azure DevOps; performed A/B testing and presented insights to executives; integrated GenAI into analytics workflows and ensured governance.