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  The Operations Research (OR) Analyst - 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.   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