Gabriele Usan
Senior Data Scientist
San Francisco, CA, US
Gabe Usan is a property and casualty data scientist. He is based in the San Francisco office of Milliman and joined the firm in 2020. Within the practice, he leads the R&D initiatives related to the intersection of risk management and climate change.
Experience
Gabe’s areas of expertise include:
- Performing predictive modeling for insurance pricing, underwriting, conversion, retention, pay equity, and claims analysis
- Developing commercial auto telematics pricing scores using machine learning
- Developing API software for point-of-sale quote and portfolio scoring
- Using catastrophe models for natural catastrophe risk analysis and pricing development
Publications and Presentations
Gabe has published a paper about “Statistical Methods for Imputing Race and Ethnicity,” and an article on the use of “Catastrophe models for wildfire mitigation.”
Education
- BA, Business Administration – University of Eastern Piedmont, Italy
- MS, Applied Economics – University of San Francisco
Publications
Read their latest work
Article
Statistical methods for imputing race and ethnicity
29 April 2024 - by Larry Baeder, Erica S. Baird (formerly, Erica Rode), Peggy Brinkmann, Joe Long, Caleb Stracke, Kweweli Togba-Doya, Gabriele Usan, Meseret Woldeyes
Imputation is a powerful tool for studying the disproportionate impact of race and ethnicity on insurance, so we discuss some uses and limitations.
Article
Catastrophe models for wildfire mitigation
04 November 2022 - by Peggy Brinkmann, Nancy Watkins, Cody Webb, David D. Evans, Gabriele Usan, Michael Glavan, Lillian Zhang, Carolyn Prescott, Tom Larsen, Grace Lee