Health Computational Modeler

Booz Allen Hamilton•Bethesda, MD

1d•$69,400 - $158,000•Remote

About The Position

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.

Requirements

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 To Haves

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

Responsibilities

Design, develop, and maintain advanced computational models focused on resource allocation, infectious disease dynamics, outbreak forecasting, and response planning.
Translate complex epidemiological data into actionable insights by building robust models, integrating data sources, and developing reliable, scalable simulation workflows.
Provide technical leadership across modeling initiatives.
Establish best practices for model development and validation.
Improve model performance and reliability.
Collaborate with epidemiologists, data scientists, engineers, and other cross-functional partners.