Operations Research / Systems Analyst - Modeling & Simulation

Requirements:

• 8+ years of progressive, hands-on operations research experience applying queueing theory, simulation, statistical modeling, and predictive analytics to real-world operational challenges.
• 3–5 years supporting DoD or Intelligence Community missions, such as personnel vetting, industrial security (NISP), counterintelligence, or insider threat.
• Bachelors degree in Operations Research, Applied Mathematics, Statistics, Industrial Engineering, or a related quantitative discipline.
• Expert knowledge of queueing theory and discrete-event simulation, with the ability to model complex operational processes.
• Practical experience with simulation tools such as Arena, AnyLogic, SimPy, or similar.
• Strong grounding in statistical modeling, hypothesis testing, experimental design, and time-series analysis.
• Hands-on proficiency in Python, R, or SAS, including statistical and machine learning libraries.
• Demonstrated ability to build and validate predictive models that forecast operational outcomes.
• Experience analyzing complex, imperfect real-world datasets, including missing data, inconsistent formats, and temporal misalignment.
• Ability to turn analytical findings into objective, data-backed recommendations for strategic decisions.
• Experience working in secure, classified government environments.
• Secret clearance required, either active or obtainable.
• Preferred: Advanced degree in Operations Research, Applied Mathematics, Statistics, Industrial Engineering, or a related quantitative discipline.
• Preferred: Familiarity with NISP, clearance adjudication, or insider threat and counterintelligence analytic frameworks.
• Preferred: Experience with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch for anomaly detection and pattern recognition.
• Preferred: Knowledge of Bayesian methods and uncertainty quantification.
• Preferred: Experience with Monte Carlo simulation and stochastic modeling.
• Preferred: Familiarity with agent-based modeling and model verification and validation practices.
• Preferred: Experience with visualization tools such as Tableau, Power BI, matplotlib, or seaborn.
• Preferred: Knowledge of optimization methods, including linear programming and heuristics.
• Preferred: SQL and database querying skills for modeling data preparation.
• Preferred: Experience with feature engineering and data preparation for statistical and machine learning models.

Responsibilities:

• Develop queueing models and discrete-event simulations to find bottlenecks and inefficiencies in personnel vetting, facility inspection, and investigative workflows.
• Recommend process improvements that shorten turnaround times while preserving quality and compliance standards.
• Use scenario analysis and what-if modeling to assess proposed process or policy changes and resource reallocations.
• Build simulations that account for variation, resource constraints, and operational policies to generate realistic forecasts.
• Apply statistical analysis and risk modeling to prioritize assessments, deploy resources effectively, and identify emerging risks or threats.
• Use advanced mathematical and statistical methods to identify anomalies, patterns, and trends in large, complex, disparate datasets.
• Develop predictive models to forecast workload, prioritize cases, and support responses to emerging conditions and threats.
• Apply machine learning methods—including classification, clustering, anomaly detection, and pattern recognition—in support of counterintelligence and insider threat missions.
• Validate model assumptions and results using historical operational data and subject matter expert input.
• Perform sensitivity analyses to assess model behavior under different assumptions and parameter values.
• Quantify and communicate uncertainty in model predictions and recommendations.
• Document modeling methods, assumptions, and limitations to support transparency and reproducibility.
• Coordinate with data engineering specialists to define analytical dataset requirements and confirm data suitability for modeling.
• Convert analytical outputs into objective, data-driven recommendations for strategic and operational decisions.
• Present complex modeling results to technical and non-technical audiences using visualizations and clear explanations.
• Contribute to cross-functional team activities, uphold technical standards, and share knowledge.

Technologies:

• Support
• Machine Learning
• Power BI
• PyTorch
• Python
• SAS
• SQL
• Security
• Tableau
• TensorFlow

More

We are N2IA Technologies, a consulting company supporting federal clients with acquisition and contracting, cost and FinOps, and technology optimization. We provide tailored strategies, software solutions, and operational support, including financial and compliance-focused solutions. In this role, you will support a federal agencys personnel vetting, industrial security, and counterintelligence operations through modeling, simulation, statistical analysis, and predictive analytics. The annual pay range is $165,000–$195,000.

last updated 43 week of 2026