Worked on C3 AI's industrial reliability platform, building features that help enterprises monitor and maintain critical infrastructure like oil rigs and manufacturing facilities.

Key contributions:

Led development of a risk scoring engine that calculates asset health across complex hierarchical structures (2,000+ nodes), re-architecting the calculation approach to achieve 50% performance improvement through multi-threaded processing.

Built an interactive 3D visualization feature in React that allows engineers to explore facility models and identify reliability issues, integrating file upload handling and AWS infrastructure.

Optimized 10+ API endpoints on the Performance Resolution team, ensuring sub-3-second response times for client-facing services.

Established comprehensive test automation coverage (150+ tests) while gaining deep understanding of the platform architecture.

Key contributions:

Drove migration of financial instrument profiles from a monolithic Java application to a modern Spring Boot/Angular stack, making it significantly easier to onboard new asset classes and expand platform capabilities.

Configured CI/CD pipelines in TeamCity to streamline deployments and ensure consistent releases across environments.

Joined during the peak of COVID-19 and worked remotely on modernizing Deutsche Bank's financial analytics platforms, helping migrate legacy systems to scalable cloud-ready architectures.

Key contributions:

Built an Angular-based data quality dashboard that automated manual data cleaning workflows, reducing analyst effort by 31% and improving productivity across the team.

Expanded test automation coverage by 27% using Protractor and Cucumber, helping catch integration issues earlier in the development cycle and reducing time to fix defects by ~40%.

Six-month internship working on ESG (Environmental, Social, Governance) tools and internal automation at BlackRock's Mumbai office.

Key contributions:

Automated a legacy ESG reporting process by migrating VB scripts to Python with HTML/CSS templating, reducing daily report generation time from 20 minutes to 4 minutes (5x improvement) and cutting codebase size by 39%.

Developed a prototype ESG risk assessment web application using Angular and Flask, creating an interactive interface for portfolio-level risk analysis.

This was my first real exposure to production systems at a major financial institution, where I learned the importance of code quality, testing, and building solutions that non-technical users can actually use.

Started as a summer intern and was asked to continue as a contractor after demonstrating strong results. Worked on data pipelines and built my first machine learning model in a production context.

Key contributions:

Migrated a legacy ETL pipeline from VB/SQL Server to Python/Oracle SQL, reducing processing time from 8 hours to 40 minutes (12x improvement) while making the codebase significantly more maintainable. Worked closely with DBAs to optimize database queries and design the new architecture.

Built a mutual fund classification model using Python and historical performance data, collaborating with financial analysts to select features and validate predictions.

This role taught me how to pick up new technologies quickly (learned Python on the job), work with domain experts who aren't engineers, and translate business requirements into working code.