- Predictive modeling
- Stochastic simulation
- Agent-based modeling
- High-performance computing
- Health Information Technology and Analytics
John Hotchkiss is a senior data scientist with experience in generating data science solutions to support policy decision makers in many domains, including education and epidemiology. Hotchkiss is both a methodologist and technician who seeks problems that will require solutions that draw on the intersection of those skills. Currently, Hotchkiss applies his training building agent-based models that simulate the spread of SARS-CoV-2 in educational contexts under varied transmission mitigation strategies to inform safe reopening strategies. Current clients include the University of California San Diego and the Rockefeller Foundation. He holds an M.S. in data analytics from Georgetown University.