Data Scientist (Mission Engineering)

Join CHAOS, a cutting-edge technology company focused on mission engineering. As a Data Scientist, you will be responsible for designing experimental constructs, building analytical pipelines, and communicating quantitative results to decision-makers. You will work closely with engineers and experts in various domains to ensure the rigor and reproducibility of simulated, experimental, and tactical results. This is a foundational hire, and you will have the freedom to set the standards for quantitative analysis from day one.

• Statistical methodology ownership for the Mission Engineering team, including experimental design and uncertainty characterization.
• Building and owning scalable Python-based data pipelines for statistical analysis and visualization of large simulation datasets.
• Mentoring peers and cross-functional teams on experimental design, statistical methodology, and reproducible analysis.
• 7+ years applying advanced statistical and data science methods, ideally supporting defense, intelligence, or advanced technology programs
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance
• Exceptional written and verbal communication skills, especially in translating quantitative approaches and results for non-technical audiences
• Strong proficiency working in Python, including scientific computing and ML libraries (especially Pandas, Polars, NumPy, SciPy, Scikit-Learn, Statsmodels, PyMC, Matplotlib, Seaborn, CuPy, PyTorch), and exposure to MATLAB or R
• Exceptional data visualization skills and the ability to develop briefing-quality technical products
• Comfortable working with Linux operating systems and writing scalable scripts/software
• Bachelor's degree or higher in Statistics, Data Science, Mathematics, Artificial Intelligence, a related quantitative field, or equivalent demonstrated expertise in modern statistical methodology
• Strong software development practices: version control, code review, reproducible workflows, and informed use of AI-assisted coding tools
• Track record of working independently, taking ownership of ambiguous problems, and delivering with minimal oversight
• Deep working expertise in experimental design, regression and Bayesian methods, uncertainty quantification, and surrogate modeling, not just textbook familiarity
• Demonstrated experience building scalable analytical pipelines for large datasets, including comfort with terabyte-scale data and modern dataframe tooling
• Master's or PhD in Statistics, Data Science, Mathematics, Artificial Intelligence, or a related quantitative field
• Direct experience applying statistical methods to outputs from military simulations including high fidelity engineering models, war games, and engagement or mission-level combat simulations such as AFSIM, ESAMS, Brawler, or Ansys STK
• Expertise designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting full kill chain or system effectiveness assessment
• Experience in developing surrogate models, simulations, machine learning, or artificial intelligence models for engineering and operations analysis applications
• Familiarity with sensor performance analysis (radar, EO/IR, RF, acoustic), weapon effectiveness analysis, or mission-level engagement analysis
• Experience with HPC environments and distributed computing frameworks (including scalable cloud services and GPU-accelerated computing)
• Leadership experience: mentoring or leading project teams through complex analytical efforts
• Substantial experience in communicating statistical methods to both technical and non-technical stakeholders and decisionmakers
• Experience supporting rapid development programs for DoD contractors, combatant commands, research labs, and acquisition communities
• Active TS/SCI clearance