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Mathematical Optimization Operations Research Jobs in Ashburn, VA

Tetra Tech

Operations Research Engineer

Washington, DC · On-site

$120K - $140K/yr

... logistically optimized model * Contribute to business process design for the strategic ... Engineering, Operations Research, Statistics, Computer Science, Mathematics) or related field

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Mathematical Optimization Operations Research information

See Ashburn, VA salary details

$39.4K

$95.9K

$154.4K

How much do mathematical optimization operations research jobs pay per year?

As of Sep 2, 2026, the average yearly pay for mathematical optimization operations research in Ashburn, VA is $95,925.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,000.00 and $118,100.00 per year, depending on experience, location, and employer.

What is mathematical optimization in operations research?

Mathematical Optimization in Operations Research is the process of finding the best solution from a set of feasible options, subject to constraints, by maximizing or minimizing an objective function. It involves formulating real-world problems mathematically and using algorithms to identify optimal or near-optimal solutions. This field is widely applied in logistics, finance, manufacturing, and other industries to improve efficiency and reduce costs. Professionals use techniques such as linear programming, integer programming, and nonlinear optimization to solve complex decision-making problems.

What are some typical challenges faced by professionals in mathematical optimization operations research, and how can they be addressed?

Professionals in Mathematical Optimization Operations Research often encounter challenges such as dealing with large-scale, complex datasets and ensuring that models are both accurate and computationally efficient. Balancing the precision of theoretical models with the practical limitations of real-world data and time constraints is a common hurdle. Collaboration with domain experts and iterative model refinement are essential strategies to address these issues. Additionally, clear communication of technical results to non-technical stakeholders is crucial for successful project implementation.

What are the key skills and qualifications needed to thrive as a mathematical optimization operations research analyst, and why are they important?

To excel as a Mathematical Optimization Operations Research Analyst, you need advanced skills in mathematics, statistics, and analytical modeling, usually supported by a degree in operations research, applied mathematics, or a related field. Familiarity with optimization software (such as CPLEX or Gurobi), programming languages like Python or R, and data analysis tools is typically required. Strong problem-solving abilities, critical thinking, and effective communication help you translate complex data into actionable business solutions. These competencies are crucial for delivering efficient, data-driven strategies that optimize organizational performance and decision-making.

What are popular job titles related to Mathematical Optimization Operations Research jobs in Ashburn, VA?

For Mathematical Optimization Operations Research jobs in Ashburn, VA, the most frequently searched job titles are:

What job categories do people searching Mathematical Optimization Operations Research jobs in Ashburn, VA look for?

The top searched job categories for Mathematical Optimization Operations Research jobs in Ashburn, VA are:

Mathematical Optimization Operations Research jobs near you
Infographic showing various Mathematical Optimization Operations Research job openings in Ashburn, VA as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution, with an average salary of $95,925 per year, or $46.1 per hour.

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

N2IA Technologies

Washington, DC • On-site

$165K - $195K/yr

Full-time

Re-posted 6 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.

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