- Leading architectural redesign and engineering of an AI-powered ad-strategy toolkit, refactoring a Django-based application to use modern frontend tools for improved UX and performance.- Engineered an asynchronous data fetching and analysis pipeline using asyncio and RabbitMQ, reducing report generation time by over 90% and enhancing system scalability.- Implemented OpenAPI and DRF-Spectacular to streamline API documentation and automatically generate client code with openapi-ts, ensuring seamless communication between backend and frontend components.- Integrated user management and payment with NextAuth with Stripe, a comprehensive marketing data dashboard for real-time performance insights.

• Designed a full-stack SPA with Next.js and Typescript, allowing users to monitor and configure Kubernetes clusters with a streamlined interactive UI utilizing open-source visualization libraries.• Engineered a Kubernetes cluster observability and alerting application, leading standups to ensure team alignment on project goals and progress, conducting code reviews and mentoring more junior members.• Developed the Kubernetes Performance Metrics Platform, integrating Kubernetes and Prometheus APIs to enable collection of real-time and time-series data on key cluster metrics resource utilization, network traffic, and response times.• Authored a 100% TypeScript codebase enabling symmetrical API type checking, efficient auto-completion, and minimizing regressions in frontend and backend deployment.• Ensured Jest snapshot testing, assertions, and mocking to ensure comprehensive unit and integration testing.

• Employed Python to streamline asset workflows and develop pipeline tools including a shader network porting system, integration Google Translate APIs for asset adaptation, and optimizing data collection for training Stable Diffusion models.• Developed procedural tools for advanced Character FX and animation setup using industry-leading software, contributing to open-source C++ plugins for high-performance rigging, and scripting for Unreal Engine in collaboration with animators.

•Authored financial workflows with Python and Scikit-Learn, producing yield curve noise metrics for volatility prediction. •Extended open-source C++ library QuantLib with new numerical methods, speeding up processing of high-frequency Treasury data by over 60% and greatly improving stability, on top of a 5x speedup using Dask.•Communicated insights using Matplotlib to create reproducible time-series data visualizations.

Collaborate one-on-one with economists to develop original economic theory and write papers for to be published in academic journals, primarily working in MATLAB, R, C++, Stata, and Excel.