> Markdown version of [/jobs/ext/4014389-data-scientist-simulation-secret-cleared](https://www.wearedevelopers.com/jobs/ext/4014389-data-scientist-simulation-secret-cleared). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - Simulation (Secret cleared) - **Company:** Accenture - **Location:** Arlington, VA, United States - **Salary:** $89,000 - $170,200 - **Contract:** Permanent contract - **Skills:** Python (Programming Language), Machine Learning, Scientific Computating, Palantir Foundry, Modeling and Simulation, AnyLogic - **Published:** October 29, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3479358163&tx=KL5757FFI&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Bachelor's degree in Statistics, Data Science, Operations Research, Industrial Engineering, Applied Mathematics, or related field * Experience in statistical and simulation modeling, SimPy/AnyLogic/Mesa/SALib or similar * Strong Python programming skills for statistical/scientific computing * Ability to work full-time onsite in the DC area * Must have an Active Secret clearance * Must be a US Citizen Preferred experience: * Experience with linear/mathematical optimization or operations research * Experience with Palantir Foundry data science tooling. * Healthcare or public sector domain experience ## Description * Design and tune statistical simulation models (e.g., Monte Carlo, Discrete Event, Agent-based modeling) underlying platform scoring. * Build predictive and forecasting models, including time-series forecasting, to identify future operational trends. * Conduct uncertainty and sensitivity analyses to quantify confidence in model outputs. * Partner with subject matter experts to validate model assumptions and improve accuracy over time. * Benchmark simulation and forecasting models against optimization-based approaches to ensure model validity and cross-validation. * Evaluate opportunities to apply machine learning as historical data becomes available.