Summary
Jeff Sauer is a research scientist and spatial data scientist with eight years of experience applying spatial statistics, GIS, and epidemiology to public health and environmental problems. Currently supporting NYC’s drug checking program, he blends PhD-level geographic information science with hands-on data engineering and statistical programming in R, Python, SQL, and cloud platforms. His work spans algorithm development for large sensor and remote-sensing datasets, reproducible GDS workflows, and publication-quality evidence synthesis on health inequalities and the U.S. opioid epidemic. A persistent open-source contributor to spatial tools (including PySAL) and a former builder of production geospatial algorithms, he pairs academic rigor from UMD and LSHTM with practical program delivery in city and startup settings. Notably, he has processed terabyte-scale movement and administrative health data and built multilevel analytical pipelines that bridge policy-facing reports and reproducible research.
8 years of coding experience
9 years of employment as a software developer
Master of Science (MSc) Epidemiology, Master of Science (MSc) Epidemiology at London School of Hygiene and Tropical Medicine, U. of London
Doctor of Philosophy - PhD Geographic Information Systems and Remote Sensing, Doctor of Philosophy - PhD Geographic Information Systems and Remote Sensing at University of Maryland
Bachelor's degree Geography (Honours thesis-based), Bachelor's degree Geography (Honours thesis-based) at McGill University
English