Job Description
CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com . About the Team: Mission Engineering at CHAOS turns simulation output into decisions. We run large-scale modeling and simulation campaigns across all warfighting domains and the full kill chain, against named threats, in operationally relevant scenarios, at the speed engineering, operational, and customer teams actually need. Every CHAOS engineering trade, pursuit, and customer engagement is anchored in rigorous, physics-based, tactically relevant, and statistically valid analysis, and we're scaling the function to meet that bar across a growing product portfolio. About the Role: On the Mission Engineering team at CHAOS, you will design, develop, execute, analyze, and validate models and simulations to deliver operational analysis and system performance assessment across defense, national security, and commercial programs. You will have freedom to move rapidly and use your expertise to apply rigorous statistical methods to analyze simulation outcomes, quantify system effectiveness, and communicate actionable insights to technical teams, leadership, and customers. Your work will directly inform critical decisions around sensor performance, mission planning, weapon effectiveness, and platform capability evaluation. This is a foundational hire. You will shape how CHAOS does mission analysis from day one, and you will have the freedom to move fast. What You'll Do Scope, plan, and execute modeling and simulation efforts and studies aligned to program objectives, managing your competing priorities and timelines effectively. Develop, configure, and execute analysis using mission-level models and simulations such as AFSIM, ESAMS, Brawler, Ansys STK, and/or physics-based models to evaluate system and platform performance in operationally relevant scenarios. Build and refine models of sensors, communications systems, aircraft (including unmanned), weapons, and spacecraft within mission-level simulation frameworks. Architect, implement, and validate models of both blue and red systems, sensors, communications, weapons, aircraft, spacecraft, and ground/maritime platforms, within mission- and engagement-level simulation frameworks. Define and apply rigorous statistical methodologies to simulation results to quantify measures of effectiveness and performance to produce relevant and defensible findings for internal and external stakeholders. Develop and maintain Python-based analysis tools and pipelines for data processing, statistical analysis, and visualization. Implement technical methodology, simulation best practices, and customer engagement. Document methodology, assumptions, and findings in technical reports and briefing materials, including data visualizations, and present results to both technical and non-technical audiences. Partner with engineering, product, growth, and customer teams to translate operational questions into well-structured analytical approaches and shape new business pursuits. Push back when the framing is wrong. Minimum Requirements Bachelor's degree or higher in Computer Science, Aerospace/Software/Computer Engineering, Data Science, Statistics, Mathematics, Operations Research, Physics, or a related field. 5+ years of experience supporting defense, intelligence, or advanced technology programs through industry or government employment. Demonstrated track record leading mission-level operations analysis studies and delivering decision-quality results to senior engineering and customer stakeholders. Extensive direct experience with combat simulations such as AFSIM, ESAMS, Brawler, Ansys STK, or equivalent, including ownership of rigorous methodology, not just execution. Significant experience developing analytical tools and applying rigorous statistical methods to interpret and present results. Strong proficiency in Python and MATLAB, including standard scientific computing libraries (such as Pandas, Polars, NumPy, SciPy, Scikit-Learn, Matplotlib, Seaborn, CuPy, or PyTorch).