1

Mathematical Modeling Jobs in Alabama (NOW HIRING)

Modeling & Simulation Analyst Program Summary KBR's Missile, Aviation, and Ground Systems (MAGS ... Possess a Bachelor of Science degree in Engineering, Physics, Mathematics, or Computer Science or ...

Modeling & Simulation Analyst Program Summary KBR's Missile, Aviation, and Ground Systems (MAGS ... Possess a Bachelor of Science degree in Engineering, Physics, Mathematics, or Computer Science or ...

Modeling & Simulation Analyst Program Summary KBR's Missile, Aviation, and Ground Systems (MAGS ... Possess a Bachelor of Science degree in Engineering, Physics, Mathematics, or Computer Science or ...

Skilled at breaking down mathematical economic modeling, graphical analysis, and policy evaluation. Guides students through deriving demand curves from utility functions, analyzing firm behavior ...

Skilled at breaking down mathematical economic modeling, graphical analysis, and policy evaluation. Guides students through deriving demand curves from utility functions, analyzing firm behavior ...

Skilled at breaking down mathematical economic modeling, graphical analysis, and policy evaluation. Guides students through deriving demand curves from utility functions, analyzing firm behavior ...

Skilled at breaking down mathematical economic modeling, graphical analysis, and policy evaluation. Guides students through deriving demand curves from utility functions, analyzing firm behavior ...

Be Seen First

We are seeking a highly motivated Modeling & Simulation (M&S) Analyst to support the Missile ... Travel: * 0-10% Travel Education & Experience: * BS in Engineering, Mathematics, Physics, or ...

Showing results 41-60

Mathematical Modeling information

See Alabama salary details

$24.9K

$51.4K

$54.8K

How much do mathematical modeling jobs pay per year?

As of Aug 6, 2026, the average yearly pay for mathematical modeling in Alabama is $51,413.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,500.00 and $53,900.00 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.

What are the most commonly searched types of Mathematical Modeling jobs in Alabama? The most popular types of Mathematical Modeling jobs in Alabama are:
What are popular job titles related to Mathematical Modeling jobs in Alabama? For Mathematical Modeling jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Mathematical Modeling jobs in Alabama look for? The top searched job categories for Mathematical Modeling jobs in Alabama are:
What cities in Alabama are hiring for Mathematical Modeling jobs? Cities in Alabama with the most Mathematical Modeling job openings:
Infographic showing various Mathematical Modeling job openings in Alabama as of August 2026, with employment types broken down into 85% Full Time, 12% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $51,413 per year, or $24.7 per hour.

Modeling and Simulation Engineer: HSV-26128

deciBel Research, Inc.

Huntsville, AL • On-site

Full-time

Posted 14 days ago


Job description

deciBel Research has an immediate opening for a Modeling and Simulation Engineer in Huntsville, AL.
Position Description:
MDA Joint Integrated Fire Control is seeking Modeling & Simulation (M&S) Engineers with a background in Electrical, Aerospace, or Mechanical Engineering to join our rapidly growing Mission Engineering team. In this role, you will be the technical engineer behind our Mission Engineering analyses. You will develop, integrate, and execute complex simulations of Integrated Air and Missile Defense (IAMD) systems to evaluate end-to-end mission effectiveness under varied conditions. Work will directly translate theoretical mission architectures into quantifiable performance data, accelerating our customers' ability to make data-driven investment and modernization decisions.
Responsibilities Include:
  • Design, code, and test high-fidelity mathematical models and simulations of IAMD components (e.g., sensors, interceptors, and threat kinematics).
  • Integrate disparate system models into both real-time (e.g., Hardware-in-the-Loop/Software-in-the-Loop) and non-real-time (constructive) simulation frameworks.
  • Develop automated analysis tools and scripts to parse large simulation datasets, enabling sensitivity analysis, trade-space exploration, and the quantification of mission effectiveness.
  • Evaluate threat kinematics, sensor-shooter assignments, weapon flyouts, and overall lethality to quantify end-to-end performance across complex IAMD architectures.

Education Requirements:
Bachelor's degree in Electrical Engineering, Aerospace Engineering, Mechanical Engineering, or a closely related highly technical field.
Experience Requirements:
  • 5 to 10 years of applied engineering experience, with a heavy focus on modeling, simulation, and analytical tool development.
  • Strong programming skills required to build and integrate engineering simulations in C++.
  • Integration Expertise: Proven ability to integrate models into larger simulation architectures, managing data exchange, simulation timing, and data collection pipelines for post-run analysis.
  • Engagement Chains: Experience analyzing architectures for "sensor-to-shooter" loops and fire control closures

Special Skills Desired:
  • Experience with Docker, Podman, or similar for containerizing M&S applications
  • Experience with Army IAMD systems or Missile Defense Agency (MDA) architectures and platforms. Familiarity with the Joint Track Management Capability Bridge
  • Experience with common DoD simulation frameworks such as AFSIM, FSI, DIS, or other environments
  • Familiarity with translating operational scenarios or "kill webs" into quantitative simulation environments
  • Experience in Python, Java, Matlab, Gitlab, and/or Linux

Applicant selected must have an active Secret security clearance, with an ability to obtain a Top Secret clearance. Must be a U.S. Citizen.