Summary
Maria Kamenetsky is a collaborative scientist with 11 years of experience at the intersection of data science, statistics, and epidemiology, now a Postdoctoral Fellow in the Occupational & Environmental Epidemiology Branch at NCI. She combines rigorous training—a PhD in Epidemiology and an MS in Statistics—with practical expertise in R, Python, SAS, and C++-optimized simulations to build spatio-temporal and predictive models for public health. Maria has taught and co-developed a graduate-level spatial statistics course, provided statistical consulting across academia and government, and translated complex methods into usable tools for students and practitioners. Her work spans applied machine learning for regulatory inspection prioritization to inferential analyses for environmental and demographic problems, reflecting both methodological depth and policy relevance. A knack for optimizing computational workflows and parallel processing makes her particularly effective at scaling analyses from classrooms to large public-health datasets. Colleagues will note she pairs technical fluency with clear teaching and consulting experience, bridging research, training, and real-world impact.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Epidemiology, Doctor of Philosophy (Ph.D.), Epidemiology at University of Wisconsin-Madison
Graduate Student at Large Program, First Year Master's Sequence in Statistical Theory and Methodology, Graduate Student at Large Program, First Year Master's Sequence in Statistical Theory and Methodology at University of Chicago
Russian, Spanish