* Worked on proprietary exchange/match engine and order system to improve performance and add functionality for key new order types and features* Performed variety of migrations and maintenance updates to key production infrastructure (AWS services, PostgreSQL, Redis)* Implemented complex portfolio risk calculation logic to properly handle user funds throughout their various in-app actions* Assisted in critical improvements to proprietary pricing and automated market-making algorithms* Onboarded new engineers and oversaw their onboarding projects

* Worked with the product and engineering team to develop new user-facing features across our backend services (such as launching new sports and new game formats)* Optimized and improved real-time data streaming across platform and clients to reduce database load and improve user experience* Implemented Datadog alerting and monitoring infrastructure to improve DevOps visibility across critical production infrastructure* Implemented and re-factored key API endpoints associated with complex front-end requirements, data flow, and state management

Performed primary development on backend webhook API for customer facing chatbot, along with various support tools. This codebase acted as the "brains" of the bot and was responsible for asynchronously interacting with back office APIs, implementing custom conversation functionality, and parsing diagnostic data to troubleshoot customer issues. I also built an automated translation pipeline to convert conversation flowcharts into logic interpretable by the bot, along with an admin web server to toggle key bot features and behaviors. Designed and implemented test suites (unit and integration) for all codebases, including a deployed mock server which mimicked various back office services to simplify testing and bot development.

Completed a Bachelor of Science degree in Computer Science and Engineering with Summa Cum Laude honors.

Refactored portions of the Viasat Browser technology (https://browser.viasat.com) to develop a generalized machine learning platform. This included updating various code components, their corresponding testing infrastructure, and their corresponding deployment code (Docker and AWS) to be more modular and reusable. To demonstrate the utility of this generalized platform, I implemented a basic spam email detection machine learning project on top of it.

Continued improving upon prior internship project, working approximately 15 hours per week on top of a full academic course load. Participated in agile development with full-time engineering team, particularly focusing on bugs that were present through out the call-stack. I traced bugs manifesting in the UI throughout codebase and solved their root cause in the backend, with fixes that were approved and merged into production.

Performed Full-stack development on new web app feature retrieving and displaying metadata for each dataset object present in a user's library. Worked with AngularJS(1.5) as a front-end framework and primarily in Java for the back-end development. I updated existing back-end APIs to retrieve new info for each dataset object, and returned these new fields in a format matching that expected by front-end Javascript. Implemented the ability to dynamically retrieve which projects made use of a given dataset (which project generated the dataset, which projects used the dataset as input data), and made sure this remained persistent despite naming updates to both the projects and datasets.