I am a fundamentals-first thinker in an industry often distracted by shiny objects. My career has been defined by a single obsession: How do we use evidence to make better decisions under uncertainty?
This approach is grounded in my academic foundation: an AB in Applied Mathematics from Harvard and an MSE in Statistics & Operations Research from Princeton. That rigorous training taught me the mathematical laws of uncertainty; my subsequent 30 years in the field taught me how those laws collide with business reality.
Currently, I serve as the VP of Business Intelligence & Data Science at STARZ. I oversee the architecture that turns raw viewer behavior into actionable strategy for millions of subscribers. My teams span multiple continents, handling everything from predictive churn modeling to content valuation.
Prior to STARZ, I held leadership roles at Sony Music, Deutsch, and Publicis, working with clients like Microsoft, DirecTV, and the NBA.
I am a Professor of Practice at the University of Oklahoma because I believe the gap in our industry is not technical; it is conceptual. We have enough people who can write Python code, but we have a shortage of people who can translate that code into business value. I teach to immunize the next generation of leaders against the "black box" mentality.
Right now, I am obsessed with the Valuation of Content in an algorithmic age. As streaming models shift, the old metrics (ratings) are dying, but the new metrics (hours streamed) are insufficient. I am working on frameworks to measure the true ROI of creative assets in a subscription economy.
“Clarity is the only sustainable competitive advantage.”