Health Computational Modeler

Booz Allen Hamilton

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Bethesda, MD
Salary
$69,400–$158,000 / yr
Employment
Full-time
Posted
10 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $212k
This role $114k
$46k $287k
below market most similar roles pay here above market

This role pays less than 96% of similar roles. Most pay $173,281–$251,400 — the blue band above. At the midpoint, this role pays about $114k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Booz Allen Hamilton

Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting

Booz Allen Hamilton currently has 1662 open roles on FindRole.

Listed pay typically runs $86,800–$198,000 across 904 roles with salary data.

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At a glance

TL;DR · Health Computational Modeler

The Health Computational Modeler will design, develop, and maintain advanced computational models focused on resource allocation, infectious disease dynamics, outbreak forecasting, and response planning. Working with epidemiologists, data scientists, and engineers, you will translate complex epidemiological data into actionable insights by building robust models and scalable simulation workflows. Key responsibilities include providing technical leadership, establishing best practices for model validation, and improving performance reliability. You will utilize Python, R, MATLAB, or Julia to develop compartmental models and discrete event simulations. Required skills include statistical modeling, model calibration, data assimilation, uncertainty quantification, and writing clean, well-documented code. The role addresses critical public health problems by integrating diverse data sources to support effective disease response and forecasting strategies within a complex epidemiological framework.

What you'll do

  • Design, develop, and maintain advanced computational models for resource allocation and infectious disease dynamics.
  • Translate complex epidemiological data into actionable insights through robust modeling and data integration.
  • Build and deploy reliable, scalable simulation workflows including testing, logging, and performance optimization.
  • Apply advanced epidemiological models such as compartmental models and discrete event simulations.
  • Perform model calibration, data assimilation, uncertainty quantification, and model validation.
  • Write clean, efficient, and well-documented code for model development and data transformation.
  • Establish best practices and modeling standards for development, validation, and performance.
  • Communicate complex technical concepts to both technical and nontechnical audiences.

What we're looking for

  • 3+ years of experience in computational modeling and simulation for infectious disease events, 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, and performance optimization.
  • Knowledge of statistical modeling, model calibration, data assimilation, uncertainty quantification, and model validation.
  • Ability to provide technical leadership, establish modeling standards, and communicate complex concepts to technical and nontechnical audiences.
  • Ability to obtain and maintain a Public Trust or Suitability/Fitness determination.
  • Bachelor’s degree in Computational Science, Operations Research, Industrial Engineering, Epidemiology, Mathematics, or Computer Science.

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