Summary
Curtis Von Gunten is a data scientist with a PhD in social/personality psychology and eight years of applied experience translating complex statistical methods into production ML products for automotive and healthcare organizations. He has repeatedly improved forecasting and operational models at scale—most recently cutting backtest runtimes from hours to seconds and boosting forecasting accuracy versus an AutoML baseline by 21% at Stellantis. At Ford he built driver scoring, EV charging-fault detection that flagged 1,000+ vehicles pre-complaint, and a repair-time predictor that halved MAE, demonstrating a knack for high-impact, observable metrics. His background in psychology, neuroscience and philosophy lets him combine rigorous causal thinking and human-centered feature design with modern time-series reconciliation and big-data pipelines. Based in Ann Arbor, he brings research-grade methods to production systems and a proven ability to turn academic techniques into operational wins.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Arts (B.A.), Philosophy, Bachelor of Arts (B.A.), Philosophy at The University of Akron
Master of Arts (M.A.), Philosophy, Master of Arts (M.A.), Philosophy at University of Connecticut
University of Missouri