I'm a data scientist, economist, and machine learning engineer based in New York City.

I established the machine learning practice from the ground up at Radicle, a disruption research company incubated by Prehype with strategic investment from Dow Jones that serves some of the world’s largest firms, including P&G, Diageo, American Family Insurance, Estée Lauder, LEGO and more.

My team and I conceptualized, designed, and built the scoring algorithms and natural language systems that power Radicle's startup research and innovation discovery products. An example is Startup Anomaly Detection™, a state of the art machine learning algorithm which estimates the plausibility that a startup will have a liquidity event such as an IPO or acquisition. Another is the Investor Cluster Score™, a feature which evaluates the signal generated from company capitalization tables. My team is also behind the recently released working paper and online econometric model that enables anyone in the world to approximate an undisclosed startup valuation with just two inputs.

We publish our research via the Journal of Empirical Entrepreneurship, a new outlet for data-driven insights on startups and venture capital, where I serve as Editor-in-Chief.

Don't hesitate to reach out if you'd like to say hello!