Overview In this role you will lead the scientific modeling and simulation work for UTS-related capabilities, translating data into high-fidelity analytical outputs used by commanders and operators. You will shape methodologies, validate assumptions, and develop advanced agent-based and physics-based models to assess risks and improve mission survivability. This position blends theory with practical defense applications in a cross-disciplinary team, offering a clear impact on decision support and risk management. You will work on a transition-ready capability that enhances decision-making under uncertainty.
Compensation / Benefits- robust 401(k) with company match
- mental health resources
- student loan repayment assistance
- adoption reimbursement
- pet insurance
- competitive total rewards package
Responsibilities- Serve as the scientific lead for computational modeling and simulation activities across the program
- Establish methodologies for representing UTS phenomena within analytical and simulation environments
- Ensure analytical approaches reflect underlying physical, operational, and statistical characteristics of the data
- Design, develop, and validate complex agent-based models representing UTS interactions and environments
- Develop agent behaviors, environmental conditions, interaction rules, and emergent system dynamics
- Evaluate simulation outputs for realism, repeatability, and operational relevance
- Evaluate government-provided datasets to identify meaningful relationships
- Develop scientifically valid feature engineering and diagnostic vector identification
- Collaborate with data scientists to ensure ML models use meaningful features rather than spurious correlations
- Assess data quality, completeness, and limitations
- Apply statistical, probabilistic, and computational methods to characterize uncertainty and system behavior
Key requirements- US Citizen with active TS/SCI clearance and ability to obtain CI Poly
- 12+ years of relevant experience
- Master's or PhD in physics, mathematics, statistics, operations research, engineering, science, or related discipline
- Strong technical leadership experience
- Extensive experience with process, predictive, physics-based, and agent-based modeling
- Recent modeling experience using statistics for predictive modeling and physics-based sensor capability assessment in synthetic scenarios
- Experience with diverse UTs data sources
- Proficiency in Python and scientific computing libraries
- Experience with AI/ML programs
- Excellent written and verbal communication skills
- On-site work in Herndon, VA
- strong technical leadership
- clear written and oral communication
- ability to collaborate with cross-functional teams
- Python and scientific computing libraries
- agent-based modeling
- statistical and probabilistic modeling
