Ryan holds a PhD in physics from the University of Virginia, where his research focused on optical quantum computing, graphene synthesis and cryonuclear physics. His first exposure to data science was while working at Thomas Jefferson National Laboratory and Duke University, where he used machine learning to identify subatomic particles for scientific experiments. His primary interest is focusing his skills on S&P Global’s world class data sets, distilling real world value and solving business problems for our customers and employees. He lived in Connecticut all his life until moving to Charlottesville for graduate school, and his favorite past time is shoveling a driveway full of waist-high, powder-white snow in the quiet, New England night.