Lee leads the science team at Zilliant, where he is responsible for the development and implementation of Zilliant’s science methodologies across the full suite of product offerings. Lee has a passion for all things data science, statistical computing and optimization. Over the past decade, he has a proven track record of transforming data into measurable financial results. Prior to Zilliant, Lee was a quantitative risk manager at JPMorgan Chase where he helped define the bank's risk capital methodologies following the 2008 financial crisis. He holds an MS and BS in Operations Research from Columbia University and an MS in Computational Finance from Carnegie Mellon University.