Kasey Jones is a data scientist with over four years of experience solving client problems using data analysis techniques in R and Python. He applies predictive modeling, simulation techniques, text analysis, and machine learning to produce impactful solutions. While at RTI, Mr. Jones has developed several modeling algorithms in conjunction with RTI's synthetic population. Projects include: predicting underage drinking rates in D.C., developing a social vulnerability index, and creating an agent-based model that calculates healthcare acquired infection rates for hospitals in North Carolina for the Centers for Disease Control and Prevention. Each project used RTI's synthetic population as the base population in the research. Before joining RTI, Mr. Jones worked as an analytical consultant in Washington, DC, for two years. He was the project lead and main programmer for an application that tracks undocumented immigrants through the United States. The application was presented to the Secretary of the Department of Homeland Security and is being used at the Office of Immigration Statistics.