Quantitative Analyst SETA

Requirements:

• Master’s degree or PhD in Economics, Data Science, Applied Mathematics, or a related quantitative field.
• 5+ years of relevant experience in quantitative economic modeling, advanced econometrics, and network data science/data engineering applied to complex adaptive systems.
• Demonstrated experience in large-scale data processing, multi-source data pipeline integration, and managing structured/unstructured data architectures.
• Practical experience with graph analytics, network modeling tools, and interconnected data architectures (e.g., Python/R quantitative libraries, graph databases, or network science frameworks).
• Strong background working within or alongside the U.S. Intelligence Community (IC), including familiarity with IC mission environments, data workflows, and intelligence-derived datasets.
• Understanding of diverse data sources across global economics, financial networks, trade flows, defense industrial supply chains, and multi-INT sources.
• Strong communication skills—both written (including executive PowerPoint briefs) and oral—with the ability to translate complex econometric and data models for senior defense stakeholders.
• Top Secret clearance with SCI eligibility.
• Preferred:
• Active Special Access Program (SAP) access and experience working at TS/SCI and SAP levels.
• Experience with defense industrial base analysis, economic statecraft, strategic competition modeling, or macroeconomic resilience metrics.
• Hands-on experience building decision-support tools, AI/ML-enabled analytical tools, cloud data engineering workflows, or large language model (LLM) research pipelines.
• Prior background supporting new program start-ups, pilot demonstrations, and transition pathways within defense or intelligence organizations.
• Experience in high paced private sector quantitative production environments such as systematic investing or trading, real time ad technology development or pharmacological optimization and customization.
• Demonstrated ability to bridge communication and technical execution across academic economists, data engineers, software developers, and operational intelligence analysts.