At Retail Scientifics, I lead end-to-end development of custom data science and AI solutions, from problem definition and model architecture through deployment and ongoing enhancement. I build predictive decision systems for market planning, site selection, pricing, and customer analytics.
My location and network models combine financial performance history, demographics, competition, foot traffic, and spatial relationships. These systems have scored 100,000+ candidate locations and quantified standalone and network-adjusted performance.
Before Retail Scientifics, I led a causal inference and experimentation team at Intuit and advanced through analytics roles at Petco, ultimately leading a predictive modeling and segmentation team. I hold a PhD in Computational Statistics and have taught business statistics at San Diego State University.

