Mike is the Chief Data Scientist for PersonaGraph, where he leads the Data Science and Machine Learning Operations teams, building the inference models populating the PersonaGraph user-understanding platform. Prior to PersonaGraph, Mike served as Director of Data Sciences for Sears Holdings. He began his career in academia teaching at the University of Pittsburgh and serving as a mathematics teaching fellow for Columbia University. His research focused on developing the epsilon-anchor methodology for resolving both an inconsistency he highlighted in the dynamics of Einstein’s general relativity theory and the convergence of “large N” Monte Carlo simulations in Statistical Mechanics’ universality models of criticality phenomena.
In this part-time course, students learn to build robust predictive models, test their validity, and clearly communicate resulting insights.