About

I'm an AI transformation and data infrastructure operator. I go into messy, data-heavy industries and rebuild the systems underneath, so the data can finally be trusted and used. My work has spanned real estate, mortgage, insurance, and consumer credit.

My career has followed one thread: finding structural inefficiency in large markets and building technology to collapse it. At McKinsey, I learned how to measure businesses. At Mubadala, I helped manage $1.5B in semiconductor capacity expansion at GlobalFoundries and saw what happens when capital meets industrial-scale engineering. At Staircase and Elephant, I raised $33M from Bessemer Venture Partners, built an engineering team of 150 across four continents over six years, and built a vertically integrated data utility that proved out on Florida's 10.5M properties at 100x cheaper than incumbents.

I studied economics at Harvard (cum laude) and earned my MBA at Columbia Business School, where my team won the Venture Capital Investment Competition. I was a Rhodes Scholarship State Finalist. Before any of that, I was a varsity 400m runner who learned that the only scoreboard that matters is the one you can measure.

Today I'm interim Chief Data Officer at a Point72/Värde-backed specialty finance platform, where I rebuilt the platform, product, and data stack and took a $120M+ run-rate business from unprofitable to profitable. Lately I'm being pulled back toward deep tech and the physical sciences, where the hard part is the technology itself.