I am a senior software engineer at Netflix, where I lead the firm's Global Real-time Guardrails initiative and currently serve as the interim lead engineer for the Data Foundations Squad within the Experimentation and Causal Inference Platform. Global Real-time Guardrails is the automated canary analysis system used during Big Bet live events and continuous application deployments, and the Data Foundations squad owns the mission-critical data pipelines that power Netflix's experimentation platform. My focus across both efforts is the strategy, correctness, and reliability of the data and tooling that Netflix data scientists rely on to run experiments at scale. I also serve as a co-Informed Captain for the Experimentation Platform's generative AI strategy, and have designed and architected agent-based systems that now run in production. I previously co-chaired the Netflix Platform Engineering UI Roundtable.
Before Netflix I spent more than a decade in finance building electronic trading systems. I worked at both Citadel — the hedge fund — and Citadel Securities, the market maker, which are two separate companies. At Citadel I built software for the Global Commodities and Global Equities desks, including charting libraries, real-time dashboards, the order entry application the entire firm uses to execute live market orders, and a Python library that lets traders create interactive charts in three lines of code. At Citadel Securities I designed and engineered the desktop trading applications for the ETF Market Making desk — every manual equity and commodities trade on that desk ran on software I wrote — and I built the RFQ system used by the Options, OTC, and ETF desks, which was the only system that did not fail during the COVID crash of 2020. I also created a market anomaly detection system that has contributed several million dollars in incremental PnL since launch. Across both firms I worked extensively with KDB+ and q in production, integrating real-time and historical time-series data into trading applications and building Python tools that let quantitative researchers query KDB+ directly from Jupyter notebooks. Earlier in my career I held engineering roles at Goldman Sachs, Morgan Stanley, BlackRock, J.P. Morgan, and S&P Capital IQ, and I began my career as a quantitative analyst working on structured finance and exotic fixed-income derivatives, including swaps, swaptions, and synthetic CDOs.
I have been speaking at conferences since 2013, including Node Congress, JSNation US, JSConf India, and DevOps.js, and I have given invited talks at the White House, the United Nations, Harvard Business School, Columbia University, New York University, and the Japan Information Technology Services Industry Association. I am the author of Learn Algorithmic Trading with Python (Apress/Springer) and the open-sourced TensorFlow.js Quickstart Guide, and I write papers on AI applications in finance — portfolio optimization, reinforcement learning for trading, and the evaluation of large language models on programming tasks, among other topics. My work has been covered in TechCrunch, Fortune, Forbes, CNN/Money, Black Enterprise, and other outlets.
My wife Felicia and I co-founded Code Crew in 2013. It began as a weekly study group in New York City coffee shops and has grown into one of the city's largest technology communities, with more than ten thousand members across two meetup groups, through which we have taught thousands of people to code. I have also taught web development at Columbia University; at the New Jersey Institute of Technology, where I worked with the mayor's office, the governor's office, and Code for America to develop and open-source the curriculum; at General Assembly; and at Startup Institute.
I hold a Bachelor of Science in Economics with a minor in Business from The Pennsylvania State University, where I was a Schreyer Honors Scholar and a Ronald E. McNair Scholar, and a Graduate Certificate in Business Analytics from Harvard Business School through the Harvard Business Analytics Program, where I graduated with Distinction. I am currently completing a Master's Degree in Data Science with a specialization in Artificial Intelligence.
Outside of work, algorithmic-trading strategy development is a long-running hobby, with most of my recent work in Python and Rust. I shoot photography on FujiFilm (after many years on Canon) and follow film closely, attending the Tribeca Film Festival and the Toronto International Film Festival each year. I once pitched a television series co-produced by Michael K. Williams, worked on independent films with Issa Rae when she first moved to New York, and toured for a year with a Grammy-nominated Universal Music Group recording artist. I am a longtime New York sports fan — Yankees, Giants, Knicks, Rangers — and a regular at the US Open, where I was in attendance when Coco Gauff won her first Grand Slam. I also follow Real Madrid, and was fortunate to be in Los Angeles when LeBron James broke Kareem Abdul-Jabbar's all-time scoring record. I live in Westchester County with my family and was born and raised in New York City.