Technical Advisor – Industrial Data Science

The Industrial Data Scientist will apply data science, operations research, and industrial economics to understand how commercial production systems behave under stress—and how they can be converted, expanded, or mobilized during crisis or conflict.

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This role focuses on uncovering latent production capacity, identifying hidden constraints, and modeling conversion pathways across OEMs and subtier supply chains. Rather than specializing in a single manufacturing technology, the successful candidate will analyze industrial systems as data-rich networks and quantify how capital, labor, materials, and time interact at scale.

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The position emphasizes commercial-industrial thinking, free from legacy acquisition assumptions, while supporting DoD stakeholders responsible for reindustrialization, stockpiling, and surge planning.

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Key Responsibilities

• Apply data science and operations research methods to analyze industrial production systems and supply chain networks.
• Model latent capacity, bottlenecks, and production elasticity across OEM and subtier ecosystems.
• Develop scenario-based models for crisis response, surge production, and industrial conversion.
• Quantify time, cost, capital, labor, and material tradeoffs associated with scaling or repurposing production.
• Analyze scale-up vs. scale-out strategies and their implications for resilience and mobilization.
• Assess industrial stockpiling strategies and replenishment timelines.
• Integrate diverse datasets (production data, supplier data, cost data, public industrial data) into coherent analytical frameworks.
• Communicate findings clearly to technical and non-technical stakeholders, including senior government decisionmakers.

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Desired Technical Expertise

• Experience in commercial manufacturing, logistics, supply chain, or operations analytics
• Experience applying data analytics, machine learning, and artificial intelligence (AI) to industrial data
• Exposure to high-volume or capital-intensive industries (automotive, electronics, semiconductors, aerospace, heavy industry, logistics)
• Experience analyzing supply chain risk, resilience, or industrial ecosystems
• Exposure to defense platforms, munitions, or dual-use manufacturing (nice to have, not required)
• Intellectual curiosity and comfort working on ambiguous, open-ended problems
• Self-starter who can both lead analytical efforts and support broader team objectives