Scott is a senior statistician in the Statistics & Data Science department at NORC. His responsibilities include providing subject matter expertise on Medicare and Medicaid (T-MSIS) data structure and policy, private insurance claims data, record linkage of survey and administrative data sources, and complex algorithm design and implementation.

Scott is currently assisting record linkage research and analysis, linking the National Center for Health Statistics (NCHS) National Hospital Care Survey (NHCS) to the National Death Index (NDI), Centers for Medicare and Medicaid Enrollment Database and claims data, HUD, and VA administrative data. He is actively researching machine learning and how it can improve large scale data linkages. Scott has been involved in several claims related projects while at NORC, allowing him to develop a deeper understanding of the policy, demographics, covered lives, and other finer intricacies of the source claims data. While at NORC, Scott has been actively working on complex algorithm design and parallel processing. He has successfully used what he has learned to design and develop several algorithms that have been used in healthcare claims related projects for the Agency for Healthcare Research and Quality (AHRQ) and the NCHS record linkage projects.

Prior to working with NORC, Scott worked for AdvanceMed and NCI company where he conducted large-scale analysis with Medicare and Medicaid data to identify fraud, waste, and abuse in the programs. While at AdvanceMed, Scott actively developing SAS programs that were used to proactively identify fraud, waste, and abuse in the Medicare and Medicaid programs. He attended several meetings where he presented his work to the state Medicaid programs and law enforcement. He worked with other analysts to build automated algorithms that could be used by non-SAS users to produce needed summaries for investigations. He was also responsible for a small team of analysts who fulfilled ad-hoc data requests made by investigators.