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Operations Research​/Systems Analyst; ORSA - Modeling and Simulation

Job in Hanover, Howard County, Maryland, 21098, USA
Listing for: SMX
Full Time position
Listed on 2026-07-23
Job specializations:
  • IT/Tech
    Data Scientist, Operations Research Analyst, Data Analyst
Salary/Wage Range or Industry Benchmark: 123000 - 206000 USD Yearly USD 123000.00 206000.00 YEAR
Job Description & How to Apply Below
Position: Operations Research / Systems Analyst (ORSA) - Modeling and Simulation (5403)
Location: Hanover

The Operations Research (OR) Analyst - Modeling & Simulation Focus provides advanced process modeling, simulation, statistical analysis, and predictive analytics across a Federal Agency's personnel vetting, industrial security, and counterintelligence operations. This position develops queueing models, discrete-event simulations, and predictive models that enable the Federal Agency to identify process bottlenecks, forecast operational outcomes, and transition from reactive reporting toward proactive, data-driven decision support.

Process

Modeling & Simulation
  • Develop queueing models and discrete-event simulations to identify bottlenecks and inefficiencies within operational pipelines (personnel vetting, facility inspections, investigative workflows)
  • Analyze and recommend process improvements that reduce turnaround times while maintaining required quality and compliance standards
  • Conduct scenario analysis and what-if modeling to evaluate the impact of proposed process changes, policy modifications, or resource reallocations
  • Build simulation models that capture stochastic variation, resource constraints, and operational policies to provide realistic operational forecasts
Statistical & Predictive Modeling
  • Apply statistical analysis and risk modeling to prioritize assessments, optimize resource deployment, and identify emerging risk or threat vectors
  • Utilize advanced mathematical and statistical modeling to detect anomalies, patterns, and trends within large, complex, and disparate data sets
  • Develop predictive models that enhance the organization's ability to forecast workload, prioritize cases, and respond to emerging conditions and threats
  • Apply machine learning techniques for classification, clustering, anomaly detection, and pattern recognition in support of counterintelligence and insider threat missions
  • Validate model assumptions and outputs against historical operational data and subject matter expert input
  • Conduct sensitivity analysis to understand model behavior under varying assumptions and parameter values
  • Quantify and communicate uncertainty in model predictions and recommendations
  • Document modeling methodologies, assumptions, and limitations to ensure transparency and reproducibility
  • Work closely with data engineering specialists to define analytical dataset requirements and ensure data suitability for modeling
  • Translate analytical outputs into objective, data-driven recommendations that support strategic and operational decision-making
  • Present complex modeling results to technical and non-technical audiences through visualizations and clear narratives
  • 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 queueing theory, simulation, statistical modeling, and predictive 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 knowledge of queueing theory and discrete-event simulation, with demonstrated ability to model complex operational processes
  • Hands‑on experience with simulation tools (Arena, Any Logic, Sim Py, or similar)
  • Strong foundation in statistical modeling, hypothesis testing, experimental design, and time‑series analysis
  • Demonstrated, hands‑on proficiency in an analytical programming language (Python, R, or SAS), including statistical and machine learning libraries
  • Proven ability to build and validate predictive models that forecast operational outcomes
  • Experience working with complex, messy real-world datasets (missing data, inconsistent formats, temporal misalignment)
  • Ability to translate analytical findings into objective, data‑backed recommendations for strategic decision‑making
  • 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, Statistics, Industrial Engineering, or a related quantitative…
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