Rachel Oidtman
Associate Principal Scientist
United States
Summary
👤
Senior🎓
Top SchoolRachel Oidtman is an Associate Principal Scientist and infectious disease modeler with 10 years of experience turning complex biological and public health data into actionable forecasts and interventions. Her work spans academia, global health, and industry—from PhD research on vector-borne disease dynamics and postdoctoral computational biology at the University of Chicago to field-facing forecasting work at UNICEF and applied data science in Medicaid at Colorado Access. She builds mathematical, statistical, and machine learning models to detect health disparities and improve emerging-disease forecasts, and she’s taught epidemiologists to code in R to bridge research and practice. Notably, she led deployment of a data assimilation algorithm for real-time Zika forecasting in Colombia and secured follow-on funding to scale efforts in Brazil. Based in the United States, she blends rigorous quantitative methods with pragmatic public-health partnerships to move models from code to policy.
10 years of coding experience
5 years of employment as a software developer
Bachelor’s of Science, Natural Resources; Statistics, Bachelor’s of Science, Natural Resources; Statistics at Cornell UniversityDoctor of Philosophy (Ph.D.), Biological Sciences, Doctor of Philosophy (Ph.D.), Biological Sciences at University of Notre Dame
English, Spanish
Github Skills (5)
infectious-diseases8
prediction-model8
machine-learning4
forecasts4
forecasting4
Programming languages (2)
Github contributions (5)
roidtman/eid_ensemble_forecasting
Feb 2021 - Jul 2022
code and data for "Trade-offs between individual and ensemble forecasts of an emerging infectious diseases"
Contributions:1 release, 2 commits, 25 pushes in 1 year 4 months
forecastingindividualensemblemachine-learningforecasts
roidtman/zika_misdiagnosis
Oct 2019 - Mar 2021
Contributions:4 pushes, 1 branch in 1 year 4 months
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