Summary
Chris Tasich is a Senior Data Scientist with a decade of experience translating environmental science and epidemiology into reproducible, production-ready analytics for federal agencies. He combines a PhD in Environmental Engineering with hands-on expertise in Bayesian statistics, numerical and agent-based modeling, and cloud-native tooling to drive decision-making under uncertainty. At the EPA he modernized legacy regulatory models—cutting runtimes by 95%—and at the CDC he supports national wastewater surveillance and genomic pipelines while standardizing CI/CD and dev environments for large analytics teams. Comfortable bridging domain and engineering teams, he builds open-source Python packages, reproducible workflows (Git, Docker), and scalable data architectures that lift organizational capacity. His fieldwork in the Ganges-Brahmaputra delta and experience running HPC clusters give him uncommon practical insight into coupled human-natural systems that informs model design and policy-relevant analyses. Based in Washington, DC, he is committed to making simple, transparent models that improve public-health and environmental regulation.
10 years of coding experience
14 years of employment as a software developer
Bachelor of Science - BS Earth and Environmental Science, Bachelor of Science - BS Earth and Environmental Science at Furman University
Doctor of Philosophy - PhD Environmental Engineering, Doctor of Philosophy - PhD Environmental Engineering at Vanderbilt University
Non-Degree Seeking, Non-Degree Seeking at University of North Georgia
English, French, Croatian