We're looking for a data scientist to build a production resource-allocation capability in Palantir Foundry.You will develop mathematical and simulation models that assemble and compare workforce teams under staffing, qualification, readiness, timing, equipment, and organizational constraints. The application will generate multiple courses of action, explain why alternatives differ, identify infeasible requests, assess organizational impact, and preserve capacity for future demands.This is a production decision-science role—not a reporting or notebook-only position. You will formulate optimization and/or simulation models, write tested Python, integrate models with Foundry Ontology and applications, and work directly with operational and domain experts.

• 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.

Here is what you need:

• 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