Roger Sarvate is an Associate of the Casualty Actuarial Society, Associate of the Society of Actuaries, and a Member of the American Academy of Actuaries, with a BA in Physics from the University of California, Berkeley, an MS in Systems Engineering from the Australian National University, and an MS in Analytics/Data Science from Dakota State University. He has over a decade of actuarial and analytical experience spanning property & casualty insurance, healthcare, and predictive modeling.

At Taylor & Mulder, Mr. Sarvate conducts detailed reviews of personal and commercial lines rate filings on behalf of insurance regulators, evaluates statistical ratemaking models for methodological soundness and regulatory compliance, and performs reserve analyses and audits for self-insured entities, captives, and insurers.

Mr. Sarvate has extensive experience in predictive modeling, including the design and evaluation of models used in ratemaking, underwriting, and econometric analysis, as well as those employed in telematics and usage-based insurance programs. He has developed and reviewed a wide range of models, including GLMs, Ridge Regression, LASSO, Elastic Net Regularization, Gradient Boosting Machines, and ensemble methods.

Prior to joining Taylor & Mulder, Mr. Sarvate held actuarial and predictive modeling roles at Liberty Mutual Group, supporting both personal and commercial lines. His technical expertise spans R, Python, SAS, SQL, VBA, Tableau, and other tools commonly used in modern actuarial practice.