Health Computational Modeler

Health Computational Modeler The Opportunity: As a Computational Modeler, you will design, develop, and maintain advanced computational models focused on resource allocation, infectious disease dynamics, outbreak forecasting, and response planning. You will translate complex epidemiological data into actionable insights by building robust models, integrating data sources, and developing reliable, scalable simulation workflows. You will provide technical leadership across modeling initiatives, establish best practices for model development and validation, improve model performance and reliability, and collaborate with epidemiologists, data scientists, engineers, and other cross-functional partners. Join us. The world can't wait. You Have: 3+ years of experience in computational modeling and simulation, including supporting infectious disease events, outbreaks, forecasting, or response planning Experience developing and applying advanced epidemiological models, such as compartmental models and discrete event simulation Experience in Python, R, MATLAB, or Julia Experience designing and deploying reliable simulation workflows, including testing, logging, monitoring, error handling, and performance optimization Knowledge of statistical modeling, model calibration, data assimilation, uncertainty quantification, and model validation Ability to write clean, efficient, and well-documented code for model development, analysis, and data transformation Ability to provide technical leadership, establish modeling standards, mentor colleagues, and communicate complex concepts to technical and nontechnical audiences Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements Bachelor’s degree in Computational Science, Operations Research, Industrial Engineering, Epidemiology, Mathematics, or Computer Science Nice If You Have: Experience leading cross-functional computational modeling or epidemiological research projects Experience deploying and operating production-grade modeling or simulation systems Experience integrating and analyzing complex epidemiological or health-related data sources, and building interactive dashboards, such as Streamlit, Shiny, or Dash, to communicate findings Experience with AI-assisted code development tools, such as Claude Code, OpenCode, or similar, to support efficient, high-quality software development Experience using cloud platforms and cloud-native services, such as AWS or Azure, for scalable modeling and data processing Knowledge of data governance, data lineage, privacy, and compliance requirements for epidemiological or health data, including tools such as Apache Atlas, AWS Glue Data Catalog, or Collibra Ability to establish software engineering best practices within modeling teams, including the use of Git for version control, automated testing, logging, and performance optimization Master’s degree in Epidemiology, Computational Science, Operations Research, Industrial Engineering, Mathematics, Computer Science, or a related Quantitative field preferred; Doctorate degree in Epidemiology, Computational Science, Operations Research, Industrial Engineering, Mathematics, Computer Science, or a related Quantitative field a plus Vetting: Applicants selected will be subject to a government investigation and may need to meet eligibility requirements of the U.S. government client.

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