During my time at Infinitus, we were focused on automating phone calls for health insurance benefit verification (BV). As one of the first engineers on the backend team, I collaborated directly with the founders, product leads, and our operations team across a variety of projects as we grew from 10 to 20 engineers and series A to B:- Scaling our offering to multiple customers required a way to efficiently validate and ingest BV tasks asynchronously. Expanding our customer-facing API, I built rule-based tools for resolving the ambiguity inherent in BV information collected from the provider.- As the volume of outbound calls increased, we needed a way to schedule them throughout the day. We had a fixed pool of resources to handle calls, and each inbound BV task came from the provider with a different deadline. The calls to complete these tasks involved insurance companies with variable open/close hours and hold times. Using a combination of heuristics and statistical modeling, I designed and implemented a system to automatically schedule and place these calls.- Running hundreds of calls simultaneously across distributed infrastructure required constant improvements to our system’s latency and fault tolerance, such as exponential backoff or cluster-wide caching. Logging, monitoring, and alerting proved crucial during system-wide outages.I had the opportunity to mentor an intern for 10 weeks during the summer of 2021. She worked on machine learning tools for the estimation of variables required by the scheduler - most notably, hold times when calling the insurance companies.

After leaving Google, I spent a year and a half building a distributed C++ intelligence capable of finding and trading patterns in the financial markets. Components of the system included: - Real-time clients to download streaming data - everything from news articles and TV broadcasts to stock ticks and analyst estimates,- A custom time-series database to ingest and store these heterogeneous market and fundamental data,- Middleware to manage trading - either simulated trading across historical data or live trading using the Interactive Brokers API,- A lightweight algorithm layer written in Python leveraging TensorFlow to train strategies using historical data and execute them using streaming inputs.To effectively design event-driven modules in C++, I built custom tools optimized for low latency without sacrificing readability. The services described above ran across multiple cores - communicating using gRPC and leveraging Prometheus for monitoring.

The click-to-call mobile ad format allows users to call an advertiser directly. Routed through Google, the call is tracked in order to provide attribution for the advertisers. Within this team, I worked on detecting and reporting various types of conversions and other call-related metrics to the advertisers. My projects included:- Adding support for a call-based charging model (as opposed to standard click-based models),- Updating data processing pipelines to display extension-level call reporting in AdWords,- Using TensorFlow-based machine learning models to identify high-fidelity conversions from call recording transcripts, and- Building an infrastructure tool for dynamically loading JavaScript workflows for call routing.While employed at Google, I conducted 120+ software engineering interviews using multiple questions across a variety of technical domains and programming languages. After each interview, I provided detailed written feedback and a recommendation to the hiring committee.

UpFor was a start-up focused on connecting users with nearby friends for offline activities. As part of Yale Entrepreneurial Institute's summer fellowship, I helped design and implement a Swift-based iOS application and a Node.js / Firebase backend.

Programming mostly in Python, I worked on Data Infrastructure at Facebook HQ in Menlo Park, California. My projects included:- Building a pipeline to predict and bound future job resource utilization from historical run-time data, and- Outlining a framework for testing distributed data processing pipelines written in Python.

CS50, offered at Yale for the first time in Fall 2015, is an “introduction to the intellectual enterprises of computer science and to the art of programming.”

Pushbyte is a group of Yale undergraduate developers working to design and engineer web and mobile experiences. I developed iOS apps, Express backends, and Angular frontends.

I helped design the admitted students website and admissions blog, as well as assisting with the general recruitment process.

oVote is a Yale startup working to build a mobile group-based voting system. I focused on the development of the iOS application.

The YEI Tech Bootcamp was a 10-week intensive introduction to Ruby on Rails web development for 30 Yale students. I gave lectures, designed homework assignments, and helped structure the course.

Honduras Children's Project is a non-profit organization dedicated to improving the education for the children of Copprome Orphanage in El Progreso, Honduras. I led both the fundraising efforts in the US and the projects on the ground in Honduras.

Breakthrough is a 6-week enrichment program for New Haven middle school students. I designed and taught a course on the economic history of the United States.