Designed and implemented full-stack internal applications (Python, React, Django), with focus on code quality, reliability, scalability and maintainability, to accelerate ML researchers, data scientists and business users velocity.

Implemented and maintained large-scale infrastructure using terraform, Docker, AWS.

Advocated and drove best practices throughout the organizations (CI/CD, Agile, security, testing, code reviews, documentation, etc.).

Supported team through interviewing, mentorship of junior members, sprint planning and team lead responsibilities.

End-to-end development of Python backend to support medical devices.

Full-stack work across backend (Python) and frontend (Typescript, React) for internal and customer-facing tooling.

Developed large-scale ETL pipelines from various data sources (excel, web, custom-formats) for automated reporting and insights generation with robust handling of customer-side schema changes.

Built and maintained real-time dashboards, visualization, analysis and recommendations for customers.

Built reproducible data standardization and data munging procedures for cross-source linking, metadata consolidation and deduping.

Handled testing and analysis of the dataset.

Proof-of-concept of cold recommendation system (i.e. for new users) based on previous activities and