About this opportunity
CHAOS Industries lists this Data Scientist, Mission Engineering opportunity in el segundo, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Responsibilities
You will own statistical methodology for the Mission Engineering team at CHAOS
You’ll design experimental constructs that extract meaningful signals from broad trade studies and computationally expensive simulation runs, build the analytical pipelines the team relies on, push the methodological state of the art on how we characterize uncertainty, build surrogate models, and communicate quantitative results to decision-makers
You will work shoulder-to-shoulder with engineers and experts in every domain to ensure that simulated, experimental, and tactical results presented by CHAOS are rigorous, reproducible, and actually deliver answers that our teams, customers, and partners need
This is a foundational hire
You will have the freedom to move fast and set the standards for how CHAOS does quantitative analysis from day one
Design rigorous experimental constructs (DOE, space‑filling designs, adaptive sampling, sequential experimentation) for large‑scale simulation campaigns, getting maximum signal per simulation hour across operationally relevant trade spaces
Apply advanced statistical methods (such as regression modeling, Bayesian inference, surrogate/metamodeling, sensitivity analysis, uncertainty quantification, and beyond) to simulation output to produce decision‑quality conclusions
Build and own scalable Python‑based data pipelines for ingestion, processing, statistical analysis, and visualization of large simulation datasets
Develop ML and statistical surrogate models that accelerate analysis, enable real‑time trade studies, and feed mission planning applications
Set team standards for data management, reproducibility, and statistical rigor (such as code review, methodology validation, and documentation practices)
Translate operational and engineering questions into well‑structured analytical approaches alongside M&S engineers, threat SMEs, and program staff. Push back when the framing is wrong
Author technical reports and briefing materials with clear, honest data visualizations; present quantitative results to senior technical and non‑technical audiences in language they can act on
Mentor peers and cross‑functional teams on experimental design, statistical methodology, and reproducible analysis
Support programs spanning DoD services, DARPA, intelligence community, and commercial customers
Benefits
Generous pre‑IPO stock option grants, relocation assistance + (coming soon!) annual bonuses
Free daily lunch, ‘No meeting Fridays’, unlimited PTO (for exempt employees), casual dress code
Life, FSA, HSA, 401k (+ Company match), and more
Medical, dental and vision benefits will be 100% paid for by the company
Qualifications
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
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Worksite address
el segundo, CA, 90245, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.