Note: The job is a remote job and is open to candidates in USA. SMX is dedicated to enabling mission success through technical expertise and innovative solutions. They are seeking an Operations Research Analyst with a focus on Optimization & Mathematical Programming to provide advanced optimization and prescriptive analytics for a Federal Agency's operations, enabling optimal resource allocation and decision-making.
Responsibilities
- 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
- 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)
- 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
- 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
Skills
- 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)
- 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
Benefits
- Health insurance
- Paid leave
- Retirement
- Learning & development opportunities
Company Overview