SETA - Complex Adaptive Systems

Summary

Complex Adaptive Systems: Clearance: TS with SCI eligibility. Active SAP eligibility preferred.Location: Arlington, VASalary: Based on experienceThe successful candidate will serve as a Quantitative Analyst SETA supporting a government program managers in the development, integration, and scaling of complex adaptive system modelling and data-intensive analytical capabilities. This role involves integrating complex, multi-source intelligence and commercial/open-source data streams into graph-based, network analytical frameworks to support strategic competition analysis, industrial base resilience, and national security decision-making.Requirements: Master's degree or PhD in Economics, Data Science, Applied Mathematics, or a related quantitative field5+ years of relevant experience in quantitative economic modeling, advanced econometrics, and network data science/data engineering applied to complex adaptive systemsDemonstrated experience in large-scale data processing, multi-source data pipeline integration, and managing structured/unstructured data architecturesPractical 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 datasetsUnderstanding of diverse data sources across global economics, financial networks, trade flows, defense industrial supply chains, and multi-INT sourcesStrong communication skills both written (including executive PowerPoint briefs) and oral with the ability to translate complex econometric and data models for senior defense stakeholdersPreferred: Active Special Access Program (SAP) access and experience working at TS/SCI and SAP levelsExperience with defense industrial base analysis, economic statecraft, strategic competition modeling, or macroeconomic resilience metricsHands-on experience building decision-support tools, AI/ML-enabled analytical tools, cloud data engineering workflows, or large language model (LLM) research pipelinesPrior background supporting new program start-ups, pilot demonstrations, and transition pathways within defense or intelligence organizationsExperience in high paced private sector quantitative production environment such as systematic investing or trading, real time ad technology development or pharmacological optimization and customizationDemonstrated ability to bridge communication and technical execution across academic economists, data engineers, software developers, and operational intelligence analystsResponsibilities: Oversee the design, evaluation, and application of quantitative economic models, network analysis frameworks, and graph-based data integration architecturesOversee the integration of complex, multi-source intelligence and economic datasets into scalable, operational analytical pipelinesServe as primary technical liaison between academic researchers, software engineering teams, and IC stakeholders to ensure tools align with operational requirementsAdvise leadership on program execution risks, data architecture scalability, and capability transition strategyPrepare technical documentation, program roadmaps, and executive briefs to communicate program progress and analytical findings to senior decision-makers#J-18808-Ljbffr

Job Description

Complex Adaptive Systems: Clearance: TS with SCI eligibility. Active SAP eligibility preferred.Location: Arlington, VASalary: Based on experienceThe successful candidate will serve as a Quantitative Analyst SETA supporting a government program managers in the development, integration, and scaling of complex adaptive system modelling and data-intensive analytical capabilities. This role involves integrating complex, multi-source intelligence and commercial/open-source data streams into graph-based, network analytical frameworks to support strategic competition analysis, industrial base resilience, and national security decision-making.Requirements: Master's degree or PhD in Economics, Data Science, Applied Mathematics, or a related quantitative field5+ years of relevant experience in quantitative economic modeling, advanced econometrics, and network data science/data engineering applied to complex adaptive systemsDemonstrated experience in large-scale data processing, multi-source data pipeline integration, and managing structured/unstructured data architecturesPractical 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 datasetsUnderstanding of diverse data sources across global economics, financial networks, trade flows, defense industrial supply chains, and multi-INT sourcesStrong communication skills both written (including executive PowerPoint briefs) and oral with the ability to translate complex econometric and data models for senior defense stakeholdersPreferred: Active Special Access Program (SAP) access and experience working at TS/SCI and SAP levelsExperience with defense industrial base analysis, economic statecraft, strategic competition modeling, or macroeconomic resilience metricsHands-on experience building decision-support tools, AI/ML-enabled analytical tools, cloud data engineering workflows, or large language model (LLM) research pipelinesPrior background supporting new program start-ups, pilot demonstrations, and transition pathways within defense or intelligence organizationsExperience in high paced private sector quantitative production environment such as systematic investing or trading, real time ad technology development or pharmacological optimization and customizationDemonstrated ability to bridge communication and technical execution across academic economists, data engineers, software developers, and operational intelligence analystsResponsibilities: Oversee the design, evaluation, and application of quantitative economic models, network analysis frameworks, and graph-based data integration architecturesOversee the integration of complex, multi-source intelligence and economic datasets into scalable, operational analytical pipelinesServe as primary technical liaison between academic researchers, software engineering teams, and IC stakeholders to ensure tools align with operational requirementsAdvise leadership on program execution risks, data architecture scalability, and capability transition strategyPrepare technical documentation, program roadmaps, and executive briefs to communicate program progress and analytical findings to senior decision-makers#J-18808-Ljbffr