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

Essential Duties and 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 Skills & Experience 

• 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)

Desired Skills & Experience 

• 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

Application Deadline:  July 31, 2026