I'm an economist and AI systems practitioner. I run Flamelit, where I lead consulting for data science, AI architecture, and AI strategy work across government, healthcare, and industry. I'm also Affiliate Faculty at the Raymond A. Mason School of Business at William & Mary.

Before consulting I spent five years at JP Morgan Chase as a lead data scientist in retail finance, two years as a senior director for data science, supporting projects covering clinical and population health at Parkland Center for Clinical Innovation (where I continue to support as an executive-in-residence), and hold a PhD in Economics from UT Austin. My research has appeared in Information Systems Research, INFORMS Journal on Computing, New England Journal of Medicine: Catalyst, and DESRIST conference proceedings.
While you'll read me covering several industries and initiatives, I approach with a common theme: find the signal in noisy data and noisier systems, prove the value with the kind of rigor that survives scrutiny (rather than a demo), then ship it into operation where it actually has to hold up in the real world. This site is where I write about the work -- the methods, the failures, the occasional finding worth sharing.