Summary
Peter Martin is a Senior Data Scientist with a PhD in Geochemistry and a decade of experience turning complex Earth and space science problems into actionable insights. He has spent the last several years building and productionizing ML-driven remote sensing and ETL systems at continental scales, cutting exploration search spaces by an order of magnitude and accelerating data processing from months to days. His work spans academia and industry—from leading NSF-funded teams and publishing Mars rover analysis at Caltech to developing field-deployable software that directly enabled new discoveries in mineral exploration. Skilled in Python, distributed computing (dask, xarray), and uncertainty propagation, he also maintains strong domain expertise in geochemistry and airborne geophysics. Peter is adept at translating technical uncertainty into clear recommendations for non-technical stakeholders, and he published an open-source Monte Carlo uncertainty package (HeCalc) to broaden access to robust error analysis. Based in Boulder, he combines curiosity about causal systems with practical delivery of scalable data products that de-risk high-stakes field programs.
4 years of coding experience
11 years of employment as a software developer
Bachelor of Arts - BA, Chemistry, Bachelor of Arts - BA, Chemistry at Wesleyan University
California Institute of Technology