Cal Skwerski is a manager in the Chicago office of Oliver Wyman Actuarial Consulting, Inc. He has been with the company for 5 years and specializes in Predictive Analytics and Commercial Property/Casualty Reserving. His work in the data science and predictive modeling field has included a variety of machine learning and other advanced techniques including natural language processing and tree-based regression methods, in both R and Python. He has designed and developed dynamic claim severity and litigation propensity scoring algorithms built upon a series of predictive models and adaptable to daily data intake.

Most recently, Cal has worked on the production of a model-based, automated claims case reserving system and built an insurance program health and performance monitoring dashboard for a major delivery service provider.

When he's not working or studying, Cal spends much of his time outside hiking, playing sports, or just kicking back with a beer at a baseball game. He is passionate about teaching future generations and sustainability. Cal is an amateur chess player but enjoys a challenge in any game of skill and wit.