Data Scientist - Clearance Required

Responsibilities

• Develop and apply statistical, mathematical, and computational methods to analyze modeling and simulation outputs
• Support execution of trade studies and design-of-experiments approaches, including parameter sweeps and sensitivity analysis
• Process and analyze large-scale simulation datasets, identifying key drivers, trends, and relationships
• Develop models to support uncertainty quantification, risk analysis, and performance assessment
• Collaborate with trade space analysts to ensure analytical methods align with study objectives and decision needs
• Work with backend developers to integrate analytical workflows into RAPTR® and related platforms
• Develop data pipelines and scripts to support repeatable and scalable analysis
• Visualize analytical results and communicate findings to both technical and non-technical stakeholders
• Contribute to technical reports, briefings, and recommendations supporting force design and architecture evaluation
• Explore advanced analytical techniques (e.g., surrogate modeling, optimization methods, or machine learning) where appropriate

Qualifications

• Bachelor’s degree in Data Science, Operations Research, Applied Mathematics, Physics, Computer Science, or a related quantitative field
• 5+ years of experience in data science, quantitative analysis, or modeling & simulation environments
• Strong proficiency in Python (preferred) or similar analytical programming languages
• Experience with statistical analysis, including regression, hypothesis testing, and multivariate analysis
• Familiarity with data analysis libraries such as NumPy, Pandas, and SciPy
• Experience designing and executing data-driven analytical workflows
• Ability to operate in loosely defined problem spaces and adapt analytical approaches as needed
• Strong problem-solving and critical thinking skills
• Excellent communication and collaboration skills

Preferred Qualifications

• Experience supporting modeling & simulation, wargaming, or defense-related analytical efforts
• Familiarity with design of experiments (DOE), optimization techniques, or Monte Carlo methods
• Experience developing surrogate models or reduced-order models for complex simulations
• Exposure to space domain problems (e.g., orbital systems, satellite operations, mission analysis)
• Experience with data visualization tools such as Matplotlib, Plotly, or similar
• Familiarity with cloud-based or distributed computing environments
• Advanced degree (M.S. or Ph.D.) in a relevant quantitative field