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Mathematical Programming Jobs (NOW HIRING)

Senior MIP Developer (Global Remote)

$55.75 - $73.75/hr

Lead the development and enhancement of algorithms to solve various mathematical programming problems, such as LP, QP, QCP, MILP, MIQP, MIQCP, etc. * Collaborate closely with a small team of highly ...

PythonRMATLABMapleVisual BasicOr another approved mathematical programming language.Experience with logical operations, set theory, and advanced quantitative analysis.Strong analytical skills in ...

Mathematical and statistical programming languages such as Python, R, MATLAB, Maple, or Visual Basic. * Apply advanced quantitative methods, including longitudinal analysis, predictive modeling ...

Mathematical and statistical programming languages such as Python, R, MATLAB, Maple, or Visual Basic. * Apply advanced quantitative methods, including longitudinal analysis, predictive modeling ...

Mathematical and statistical programming languages such as Python, R, MATLAB, Maple, or Visual Basic. * Apply advanced quantitative methods, including longitudinal analysis, predictive modeling ...

$63K/yr

OR COMBINATION OF EDUCATION AND EXPERIENCE: at least 24 hours of mathematics and statistics ... Experience in administrative aspects of task engineering and management, e.g., procurement policies ...

$63K/yr

OR COMBINATION OF EDUCATION AND EXPERIENCE: at least 24 hours of mathematics and statistics ... Experience in administrative aspects of task engineering and management, e.g., procurement policies ...

Integrate advanced algorithmic techniques from mathematical programming and combinatorial optimization for real-time beam hopping and dynamic resource allocation in satellite communication systems.

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Mathematical Programming information

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How much do mathematical programming jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for mathematical programming in the United States is $39.54, according to ZipRecruiter salary data. Most workers in this role earn between $25.72 and $51.44 per hour, depending on experience, location, and employer.

What are the typical responsibilities of someone working in mathematical programming?

Professionals in Mathematical Programming are primarily responsible for developing, implementing, and analyzing mathematical models to solve complex optimization problems in areas like logistics, finance, or engineering. Their daily tasks often include formulating models, coding algorithms, running simulations, and interpreting results to advise decision-makers. Mathematical Programmers frequently collaborate with cross-functional teams such as data analysts, domain experts, and project managers to tailor solutions to organizational needs. This hands-on, collaborative role offers continuous learning opportunities and exposure to a wide variety of real-world problems, making it a dynamic and rewarding career choice.

What are the key skills and qualifications needed to thrive in mathematical programming, and why are they important?

To excel in Mathematical Programming, candidates typically need a strong background in mathematics, operations research, and computer science, often supported by a relevant bachelor's or master's degree. Proficiency in programming languages such as Python, MATLAB, or specialized optimization software like CPLEX and Gurobi is highly valued in this field. Strong analytical thinking, problem-solving abilities, and clear communication skills help professionals interpret complex data and effectively present solutions. These skills are vital for developing efficient algorithms and optimization models that solve real-world business or engineering challenges.

What is a mathematical programming?

A Mathematical Programming job involves using mathematical models, optimization techniques, and algorithms to solve complex problems in various industries. Professionals in this field work on tasks such as resource allocation, scheduling, risk analysis, and decision-making processes. They utilize programming languages like Python, R, or specialized optimization software to develop efficient solutions. Common industries that hire for this role include finance, logistics, engineering, and data science. These jobs require strong analytical skills, mathematical knowledge, and the ability to translate real-world problems into mathematical formulations.

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Cities with the most Mathematical Programming job openings:

What are the most commonly searched types of Mathematical Programming jobs?

The most popular types of Mathematical Programming jobs are:

What states have the most Mathematical Programming jobs?

States with the most job openings for Mathematical Programming jobs include:

Infographic showing various Mathematical Programming job openings in the United States as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $82,234 per year, or $39.5 per hour.

Operations Research / Systems Analyst (ORSA) - Optimization & Mathematical Programming Focus

N2IA Technologies

Washington, DC

$111K - $131K/yr

Full-time

Posted 17 days ago


Job description

Operations Research / Systems Analyst (ORSA) - Optimization & Mathematical Programming Focus

Our Company

N2IA Technologies is a consulting company specializing in acquisition/contracting support, cost/FinOps, and technology optimization for federal clients. We deliver tailored strategies, robust software solutions, and streamlined operations to help organizations achieve their goals. At N2IA, we are committed to developing innovative financial and compliance-based solutions that address evolving business and regulatory needs. If you are passionate about accounting, financial accuracy, and supporting government programs, N2IA is the place for you.

Position Overview

The Operations Research / Systems Analyst (ORSA)  - Optimization & Mathematical Programming Focus provides advanced optimization, resource allocation, and prescriptive analytics across a Federal Agency's personnel vetting, industrial security, and counterintelligence operations. This position formulates and solves complex mathematical programming problems that enable the Federal Agency to optimize resource deployment, prioritize competing requirements, and transition from reactive decision-making toward mathematically grounded, optimal resource allocation strategies.

Key Responsibilities:

Mathematical Optimization & Resource Allocation

  • Formulate real-world resource allocation problems as mathematical optimization models (linear programming, integer programming, mixed-integer programming).
  • Develop and implement optimization algorithms for complex assignment problems including adjudicator workload distribution, facility inspection scheduling, and investigator allocation.
  • Apply constraint programming and heuristic methods to solve large-scale, computationally challenging optimization problems.
  • Build decision support tools that enable operational leaders to explore tradeoffs and make resource deployment decisions with mathematical rigor

Strategic Analysis & Decision Support

  • Conduct cost-benefit analyses and apply mathematical programming techniques to optimize the distribution of personnel, budgetary, and operational resources across competing requirements.
  • Apply risk-based optimization to prioritize facility assessments, case assignments, and inspection schedules based on threat levels and resource constraints.
  • Perform trade-space analysis and sensitivity studies to understand how optimal solutions change under different assumptions, constraints, or objectives.
  • Develop multi-objective optimization approaches that balance competing goals (speed, quality, cost, risk mitigation)

Model Development & Implementation

  • Utilize optimization solvers (Gurobi, CPLEX, or open-source alternatives like Pyomo, PuLP, OR-Tools) to implement and solve mathematical models.
  • Validate optimization model outputs against historical operational data and subject matter expert judgment.
  • Develop prescriptive analytics that recommend specific actions based on optimization results.
  • Create scenario planning tools that allow decision-makers to explore "what-if" questions regarding resource allocation strategies

Collaboration & Communication

  • Work closely with modeling/simulation specialists to incorporate predictive analytics into optimization formulations.
  • Partner with data engineering specialists to obtain empirically-grounded parameters, constraints, and objective function coefficients.
  • Translate mathematical optimization results into clear, actionable recommendations for non-technical decision-makers.
  • Present optimization approaches, tradeoff analyses, and recommendations to senior leadership.
  • Participate in cross-functional team activities to maintain technical standards and share knowledge.

Required Qualifications

  • 8+ years of progressive, hands-on operations research experience, including demonstrated application of mathematical optimization, resource allocation modeling, and prescriptive analytics to real-world operational problems.
  • 3–5 years of that experience supporting DoD or Intelligence Community mission areas such as personnel vetting, industrial security (NISP), counterintelligence, or insider threat.
  • Expert-level proficiency in mathematical optimization including linear programming, integer programming, and mixed-integer programming.
  • Hands-on experience with optimization solvers (Gurobi, CPLEX, FICO Xpress, or open-source alternatives such as Pyomo, PuLP, OR-Tools, COIN-OR).
  • Demonstrated ability to formulate real-world problems as mathematical programs, including objective function design and constraint identification.
  • Proven proficiency in an analytical programming language (Python or R), with emphasis on optimization modeling libraries.
  • Experience with constraint programming and heuristic solution methods for large-scale or computationally difficult problems.
  • Strong foundation in algorithm design, computational complexity, and solution methods.
  • Ability to validate optimization models using operational data and communicate results to non-technical stakeholders.
  • Experience working in secure (classified) government environments.
  • Secret clearance required (active or ability to obtain).
  • Bachelor degree in Operations Research, Applied Mathematics, Industrial Engineering, Management Science, or a related quantitative discipline.

Preferred Qualifications

  • Advanced degree in Operations Research, Applied Mathematics, Industrial Engineering, Management Science, or a related quantitative discipline.
  • Familiarity with NISP, clearance adjudication processes, and/or insider threat/counterintelligence analytic frameworks.
  • Experience with nonlinear optimization and stochastic optimization techniques.
  • Knowledge of multi-objective optimization and Pareto analysis.
  • Network optimization and graph algorithms (shortest path, max flow, matching problems).
  • Experience with scheduling and routing problems (job shop scheduling, vehicle routing).
  • Familiarity with game theory and decision analysis under uncertainty.
  • Knowledge of operations research software (AMPL, GAMS).
  • Data visualization tools (Tableau, Power BI) for communicating optimization results.
  • SQL and database querying skills to support model parameterization.
  • Knowledge of queueing theory and simulation to better integrate with modeling specialists.
  • Experience with statistical modeling and risk analysis to inform optimization formulations.

N2IA is committed to fostering a diverse and inclusive work environment. We are an Equal Employment Opportunity Employer and encourage applications from all qualified individuals, regardless of gender, race, ethnicity, sexual orientation, disability, or veteran status.