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Agent Based Modeling Jobs (NOW HIRING)

Alutiiq

Operations Research Analyst

El Segundo, CA · On-site

$215K - $250K/yr

... agent-based methods Develop and apply analytical models for cross-enterprise architecture studies, development plans, technology development efforts, and military utility studies Assess outcomes and ...

GRVTY

DoD MLOps Software Engineer

Honolulu, HI

Experience with agent-based modeling, AI-enabled simulations, decision-support tools, wargaming systems, and human-machine teaming * Proficient in domain-specific languages (DSLs), scripting ...

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How much do agent based modeling jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for agent based modeling in the United States is $30.15, according to ZipRecruiter salary data. Most workers in this role earn between $23.56 and $39.66 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Agent Based Modeling position, and why are they important?

To thrive in an Agent Based Modeling role, a strong background in computational modeling, mathematics, and systems analysis is typically required, often supported by a degree in computer science, engineering, or a related field. Proficiency with simulation tools such as NetLogo, AnyLogic, or Repast, as well as programming languages like Python or Java, is highly valuable. Effective communication, critical thinking, and strong collaboration skills help professionals explain complex models to stakeholders and work within multidisciplinary teams. These qualities are crucial for accurately simulating real-world systems, delivering actionable insights, and driving informed decision-making in various industries.

What are some typical challenges faced in an Agent Based Modeling position?

A common challenge in Agent Based Modeling is accurately representing complex, real-world systems with diverse and dynamic agents while balancing computational resources and model simplicity. Professionals in this role often need to validate and calibrate their models with limited or imperfect data, requiring both technical skill and creativity. Additionally, effectively communicating modeling results to non-technical stakeholders and integrating feedback into iterations is a key part of the job. Overcoming these challenges provides rewarding opportunities to contribute to innovative solutions across areas like finance, healthcare, logistics, or social sciences.

What is an Agent-Based Modeling job?

An Agent-Based Modeling (ABM) job involves developing and implementing simulations that model the interactions of autonomous agents within a system. These roles are common in fields like economics, epidemiology, traffic modeling, and artificial intelligence. Professionals in this role use programming and mathematical models to analyze complex systems and predict emergent behaviors. Key skills typically include coding (Python, NetLogo, or AnyLogic), data analysis, and knowledge of computational modeling techniques.

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Agent Based Modeling jobs near you
Infographic showing various Agent Based Modeling job openings in the United States as of July 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 100% In-person job distribution, with an average salary of $62,702 per year, or $30.1 per hour.
Associate Research Scientist

Associate Research Scientist

Columbia University in the City of New York

New York, NY • On-site

Full-time

Posted 23 days ago

Job description

Description
The Department of Radiology Clinical Research Division invites applications for an Associate Research Scientist to join the Center for Advanced Diagnostic Research (CADRe) of Dr. Stella Kang. The successful candidate will lead the development and implementation of advanced computational models of disease, with a focus on oral lesions and cancers.
This position involves the design, execution, and analysis of quantitative disease simulation models, including state-transition (Markov) models, discrete event simulations, differential equations, and agent-based modeling approaches. The candidate will integrate epidemiologic and clinical data from national datasets and the scientific literature into robust computational frameworks.
Specific duties include:
  • Design, develop, and validate computational disease models using state-transition, discrete event, differential equation, and agent-based modeling methodologies.
  • Implement simulation models in Python, R, C, C++, or other scientific programming environments.
  • Integrate model parameters using national datasets for incidence, mortality, and related epidemiologic outcomes.
  • Conduct structured literature reviews to inform model inputs, assumptions, and validation.
  • Apply principles of diagnostic test accuracy, including ROC analysis.
  • Perform statistical analyses, including multivariable regression and time-to-event methods, as needed to support modeling.
  • Develop and maintain databases of model inputs, outputs, and analytical results.
  • Prepare manuscripts, abstracts, and presentations for peer-reviewed journals and scientific conferences.
  • Present regular progress updates to the Principal Investigator and collaborate with a multidisciplinary research team.
  • Mentor junior researchers, including Postdoctoral Fellows and research assistants, as appropriate.

Qualifications
Minimum Qualifications:
  1. Ph.D. in decision sciences, industrial engineering, epidemiology, biostatistics, mathematics, engineering, computational sciences, or a related quantitative field.
  2. Demonstrated expertise in simulation modeling methodologies, including Markov/state-transition, discrete event, differential equation, and/or agent-based modeling.
  3. Strong foundation in probability theory and statistical methods.
  4. Proficiency in scientific programming (Python, R, C, C++, or equivalent).
  5. Experience conducting systematic literature searches using PubMed/MEDLINE, Embase, or similar databases.
  6. Excellent written and oral communication skills in a scientific context.
  7. Strong organizational skills for managing complex datasets and multi-component modeling projects

Preferred Qualifications:
  • Experience in decision analytic modeling or economic evaluation.
  • Knowledge of epidemiologic methods and health outcomes research.
  • Prior involvement in modeling cancer or oral lesion progression.
  • Experience mentoring trainees and collaborating within multidisciplinary research teams.

Apply