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Mathematical Modeling information

See California salary details

$27.1K

$56K

$59.7K

How much do mathematical modeling jobs pay per year?

As of Aug 9, 2026, the average yearly pay for mathematical modeling in California is $55,980.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,200.00 and $58,700.00 per year, depending on experience, location, and employer.

What jobs use mathematical modeling?

Mathematical modeling is used in a variety of jobs such as data analyst, operations researcher, financial analyst, and systems engineer. These roles involve creating models to analyze data, optimize processes, or predict outcomes, often requiring skills in programming, statistics, and specialized software like MATLAB or R.

What are the key skills and qualifications needed to thrive as a mathematical modeler, and why are they important?

To excel as a Mathematical Modeler, you need a strong background in mathematics, statistics, and computational science, typically supported by a degree in mathematics, engineering, or a related field. Familiarity with programming languages such as Python, MATLAB, or R, and experience with modeling software and data analysis tools are crucial. Analytical thinking, problem-solving, and effective communication skills help translate complex findings for diverse stakeholders. These abilities ensure accurate model development, insightful analysis, and impactful decision-making across scientific and business applications.

What is mathematical modeling?

Mathematical modeling is the process of using mathematical concepts, structures, and equations to represent real-world systems, phenomena, or problems. This can involve creating formulas or simulations to predict outcomes, analyze situations, or solve complex issues in fields like science, engineering, economics, and more. By abstracting key components of a problem into mathematical terms, models help researchers and professionals test ideas, optimize solutions, and make informed decisions. Mathematical modeling often requires both theoretical knowledge and practical application to ensure the model accurately reflects reality.

What is the difference between Mathematical Modeling vs Data Analyst?

AspectMathematical ModelingData Analyst
Required CredentialsDegree in Mathematics, Applied Math, or related fieldsDegree in Statistics, Data Science, or related fields
Work EnvironmentResearch labs, engineering firms, academiaBusiness, finance, marketing departments
Industry UsageDeveloping models to simulate systems or processesAnalyzing data to inform business decisions

Mathematical Modeling focuses on creating mathematical representations of real-world systems, often for simulation or prediction. Data Analysts interpret and analyze data sets to support decision-making. While both roles require strong quantitative skills and familiarity with statistical tools, Mathematical Modelers emphasize developing models, whereas Data Analysts focus on data interpretation and reporting.

What are some common challenges faced by professionals in mathematical modeling roles, and how can they be addressed?

Professionals in mathematical modeling often encounter challenges such as dealing with incomplete or noisy data, ensuring models are both accurate and interpretable, and effectively communicating complex results to non-technical stakeholders. To address these issues, it's important to regularly validate models with real-world data, collaborate closely with domain experts, and develop strong data visualization and presentation skills. Building a robust understanding of statistical methods and staying updated on new modeling techniques can also help in overcoming these challenges and delivering impactful results.

What do you do in mathematical modeling?

In mathematical modeling, a mathematical modeler develops mathematical representations of real-world systems to analyze and predict their behavior. This involves formulating equations, using computational tools, and validating models with data to support decision-making or problem-solving. Strong analytical skills and knowledge of programming languages like MATLAB or Python are often required.

How to get a job in mathematical modeling?

The qualifications that you need to start working in mathematical modeling include a degree and experience using computer software and programming languages. You can start in this field by earning a bachelor’s degree in math, statistics, or computer science. Some employers accept applicants who have previous experience and relevant computation skills. If your duties involve computer programming, you need to know languages like Python or C++. Research positions often require a master’s degree or Ph.D. If your responsibilities include data analysis, you can pursue a graduate degree in data science, machine learning, or a similar subject.

More about Mathematical Modeling jobs
What are the most commonly searched types of Mathematical Modeling jobs in California? The most popular types of Mathematical Modeling jobs in California are:
What are popular job titles related to Mathematical Modeling jobs in California? For Mathematical Modeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Mathematical Modeling jobs in California look for? The top searched job categories for Mathematical Modeling jobs in California are:
What cities in California are hiring for Mathematical Modeling jobs? Cities in California with the most Mathematical Modeling job openings:
Mathematical Modeling jobs near you
Infographic showing various Mathematical Modeling job openings in California as of August 2026, with employment types broken down into 77% Full Time, 19% Part Time, 2% Temporary, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $55,980 per year, or $26.9 per hour.

Modeling and Simulation Engineer

Maven Robotics

San Francisco, CA

Full-time

Posted 4 days ago

Job description

Role Description

We are looking to recruit an exceptional Modeling & Simulation Engineer to work on our robot models, environment models, and simulation pipeline.

In this role you will:

  • Define simulation requirements
  • Develop performant, cutting-edge mathematical models of robots, manipulators and the scenes in which they operate
  • Strike the perfect balance between fidelity and computational complexity
  • Integrate simulation-based assessment into CI/CD pipelines in a way that scales
  • Make simulation an indispensable part of our entire design, development and deployment process

You will be working closely with the Simulation, Motion Planning & Controls, Field Operations and Intelligence teams.

Qualifications

Must-have:

  • MS or PhD in engineering, mathematics, computer science or a related discipline
  • Experience in mathematical modeling of complex dynamic systems
  • Ability to take ownership of a large, strategically important development project and drive its success
  • Willingness to step in and support other teams when we have tight deadlines and problems to solve

Nice-to-have:

  • Familiarity with environments for robotic simulation including Isaac Sim
  • Experience in some combination of:
    • applied optimization
    • modeling of mechanical contact
    • creation of detailed 3D world models
    • GPU acceleration of physics simulations
    • deployment of numerically-intensive simulations to cloud compute platforms
    • integration of simulation tests into CI/CD pipelines
    • creation of simulation test cases from real-world data
    • simulation for HiL testing

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