Summary
Peter Boyd is a Senior Data Scientist and Consultant based in Seattle with a PhD in Statistics and five years of applied analytics experience supporting federal agencies and international organizations. He specializes in spatio-temporal statistical research, translating complex models into actionable insights for clients such as the US Census Bureau, USDA, Harvard Kennedy School, and UNICEF. His background spans experiment design, metric dashboards, and hands-on consulting across academia, industry, and government, demonstrating an ability to communicate technical results to non-statistical audiences. Peter's early work includes environmental and wildlife modeling using zero-inflated GLMs and spatial autocorrelation methods, and he has practical experience applying time-series and cluster analyses in corporate R&D settings. Comfortable leading projects and mentoring peers, he blends rigorous academic training with pragmatic, policy-relevant analytics. His public code and project history on GitHub reflect a researcher-practitioner who values reproducibility and open tools.
5 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at Oregon State University
Actuarial Science, Applied Statistics, Mathematical Statistics, Actuarial Science, Applied Statistics, Mathematical Statistics at Purdue University