Tom Sanschagrin

Tom Sanschagrin has a diverse work experience spanning multiple industries and roles. Tom is currently the Director of Analytics at Kemper Insurance, where they lead a data analytics team and serves as a strategic partner to the business. Prior to this, Tom was the Manager of Business Intelligence & Data Science at Infosys, where they led a team responsible for data analysis, predictive analytics, and report construction. Tom also has experience as the Data Science & Resource Planning Manager at Vanguard, where they oversaw the modernization of business intelligence and analytics capabilities. Additionally, Tom has worked as an Adjunct Professor at both Rio Salado College and Estrella Mountain Community College, teaching Business and Sociology courses respectively. Before transitioning into analytics, Tom gained extensive experience in the insurance industry, having held various roles at The Hartford, including Auto BI Department Manager, Claims Team Leader, and Bodily Injury Claim Adjuster. Overall, Tom's work experience reflects their strong analytical skills and expertise in data analysis and insight, predictive analytics, and resource planning.

Tom Sanschagrin has a Master's degree in Data Science, specializing in Predictive Analytics, which they obtained from Northwestern University in 2019. Prior to that, they completed their Master of Business Administration (MBA) in Applied Leadership & Management at Arizona State University in 2009. Tom also holds a Bachelor of Arts (BA) in Sociology and a Bachelor of Science (BS) in Political Science and Government, both earned from Arizona State University between 2001 and 2005. In terms of additional certifications, they have obtained a Project Management Professional (PMP) from the Project Management Institute in October 2019. Tom also holds a Lean Six Sigma Black Belt certification from Villanova University and Series 6 and Series 63 certifications from FINRA (Financial Industry Regulatory Authority), although it is not specified when these were obtained.