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Agent Based Modeling Scientist Jobs (NOW HIRING)

Novelis Global R&T

Modeling Scientist

Kennesaw, GA

... based approaches like large scale crystal plasticity finite element modeling and data-driven ... Broad science and engineering background and ability to connect knowledge across multiple ...

Novelis

Modeling Scientist

Kennesaw, GA · On-site

... based approaches like large scale crystal plasticity finite element modeling and data-driven ... Broad science and engineering background and ability to connect knowledge across multiple ...

Novelis Global R&T

Modeling Scientist

Kennesaw, GA · On-site

... based approaches like large scale crystal plasticity finite element modeling and data-driven ... Broad science and engineering background and ability to connect knowledge across multiple ...

Henry Ford Health System

Epidemiologist I

Detroit, MI · On-site

... agent-based modeling techniques, Epidemiological analysis methods, Statistical sampling methods, and Healthcare-associated infection surveillance methods to complete necessary tasks; conduct library ...

Augment

Principal Scientist, Data

Houston, TX

$80 - $83/hr

Data Scientist - AI/ML Focus Worksite: Onsite Monday-Thursday (Mandatory) - Houston, TX Must-Have ... model accuracy and efficiency. NLP & Agent-Based AI Applications * Build LLM-powered solutions ...

Corporate Services

Epidemiologist I

Detroit, MI

... agent-based modeling techniques, Epidemiological analysis methods, Statistical sampling methods, and Healthcare-associated infection surveillance methods to complete necessary tasks; conduct library ...

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Agent Based Modeling Scientist information

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$33K

$50.6K

$96.5K

How much do agent based modeling scientist jobs pay per year?

As of May 30, 2026, the average yearly pay for agent based modeling scientist in the United States is $50,572.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,500.00 and $49,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Agent Based Modeling Scientist, and why are they important?

To thrive as an Agent Based Modeling Scientist, you need expertise in computational modeling, systems theory, and a strong background in mathematics or related fields, often supported by an advanced degree. Proficiency with programming languages such as Python, Java, or NetLogo and familiarity with simulation software are typically required. Analytical thinking, problem-solving, and the ability to communicate complex concepts clearly are valuable soft skills in this role. These skills are crucial for accurately developing, interpreting, and conveying insights from agent-based models to inform research or decision-making.

How does an Agent Based Modeling Scientist typically collaborate with interdisciplinary teams during a project?

Agent Based Modeling Scientists often work closely with experts from fields such as economics, epidemiology, engineering, and computer science to ensure that models accurately reflect real-world systems. Collaboration usually involves regular meetings to define system parameters, validate model assumptions, and interpret simulation results. Effective communication is essential, as team members may not always be familiar with agent-based modeling concepts. Sharing insights and translating technical findings for broader audiences helps ensure models are both robust and actionable for decision-makers.

What is an Agent Based Modeling Scientist?

An Agent Based Modeling (ABM) Scientist is a researcher or professional who develops computational models that simulate the actions and interactions of autonomous agents (such as individuals, groups, or entities) to study complex systems. These scientists use ABM techniques to analyze how the behavior of individual agents leads to collective outcomes, often in fields like biology, economics, social sciences, and epidemiology. Their work involves designing models, running simulations, and interpreting data to gain insights into system dynamics and emergent phenomena.

What is the difference between Agent Based Modeling Scientist vs Data Scientist?

AspectAgent Based Modeling ScientistData Scientist
Required CredentialsMaster's or PhD in computer science, mathematics, or related fields; experience with modeling and simulationDegree in statistics, computer science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentResearch labs, academia, or industry focused on simulation and modeling projectsBusiness, tech companies, or consulting firms analyzing large datasets
Industry UsageResearch, simulation, complex systems modelingData analysis, predictive modeling, business insights

While both roles require strong analytical skills and programming knowledge, an Agent Based Modeling Scientist specializes in creating simulations of autonomous agents within complex systems, whereas a Data Scientist focuses on analyzing and interpreting large datasets to inform business decisions.

More about Agent Based Modeling Scientist jobs
What cities are hiring for Agent Based Modeling Scientist jobs? Cities with the most Agent Based Modeling Scientist job openings:
What states have the most Agent Based Modeling Scientist jobs? States with the most job openings for Agent Based Modeling Scientist jobs include:
What job categories do people searching Agent Based Modeling Scientist jobs look for? The top searched job categories for Agent Based Modeling Scientist jobs are:
Agent Based Modeling Scientist jobs near you
Infographic showing various Agent Based Modeling Scientist job openings in the United States as of May 2026, with employment types broken down into 74% Full Time, 13% Part Time, 3% Temporary, and 10% Contract. Highlights an 81% In-person, and 19% Remote job distribution, with an average salary of $50,572 per year, or $24.3 per hour.
Associate Research Scientist

Associate Research Scientist

Columbia University in the City of New York

New York, NY • On-site

Full-time

Posted 7 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.

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