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Mathematical Optimization Jobs in Laurel, MD (NOW HIRING)

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Mathematical Optimization information

See Laurel, MD salary details

$15.9K

$55.3K

$101.1K

How much do mathematical optimization jobs pay per year?

As of Aug 18, 2026, the average yearly pay for mathematical optimization in Laurel, MD is $55,318.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,700.00 and $71,900.00 per year, depending on experience, location, and employer.

What is a mathematical optimization?

A Mathematical Optimization job involves using mathematical techniques and algorithms to find the best possible solution to a given problem while satisfying constraints. Professionals in this field work in industries like finance, logistics, engineering, and artificial intelligence to optimize processes, minimize costs, or maximize efficiency. They use tools like linear programming, integer programming, and machine learning to solve complex decision-making problems.

What do mathematical optimization professionals do?

Professionals in Mathematical Optimization often work on projects involving resource allocation, supply chain management, scheduling, logistics, network design, or financial portfolio optimization. They use mathematical models to define and solve problems where the objective is to maximize efficiency or minimize costs under various constraints. Work may include collaborating with cross-functional teams to gather requirements, analyze large datasets, develop optimization algorithms, and implement solutions within existing business systems. These roles are found across industries such as manufacturing, transportation, finance, and technology, providing diverse and challenging opportunities. This variety in project scope allows for continuous learning and professional growth.

What are the key skills and qualifications needed to thrive in mathematical optimization?

To thrive in Mathematical Optimization, you need a strong background in mathematics, statistical modeling, and algorithm development, often supported by a degree in mathematics, operations research, engineering, or related fields. Proficiency with programming languages such as Python, MATLAB, or specialized optimization software (like Gurobi, CPLEX, or AMPL) is typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate complex concepts clearly are critical soft skills for this role. These skills enable professionals to design effective solutions, interpret results, and convey recommendations to both technical and non-technical stakeholders.

What are popular job titles related to Mathematical Optimization jobs in Laurel, MD?

For Mathematical Optimization jobs in Laurel, MD, the most frequently searched job titles are:

What job categories do people searching Mathematical Optimization jobs in Laurel, MD look for?

The top searched job categories for Mathematical Optimization jobs in Laurel, MD are:

Infographic showing various Mathematical Optimization job openings in Laurel, MD as of August 2026, with employment types broken down into 71% Full Time, 21% Part Time, and 8% Contract. Highlights an 100% In-person job distribution, with an average salary of $55,318 per year, or $26.6 per hour.

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

N2IA Technologies

Washington, DC • On-site

$165K - $195K/yr

Full-time

Posted 19 days ago


Job description

Operations Research / Systems Analyst (ORSA) - Optimization & Mathematical Programming Focus Our CompanyN2IA 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 OverviewThe 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 AllocationFormulate 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 rigorStrategic Analysis & Decision SupportConduct 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 & ImplementationUtilize 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 strategiesCollaboration & CommunicationWork 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 Qualifications8+ 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 QualificationsAdvanced 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.