SETA - Complex Adaptive Systems (TS Clearance)

Oak Leaf Solutions; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Complex Adaptive Systems in Arlington, VA is seeking a Quantitative Analyst SETA to support government program managers in modelling and data-intensive capabilities. You will integrate multi-source intelligence and commercial/open-source data streams into graph-based and network analytical frameworks to inform strategic competition analysis and national security decisions.

The role requires a strong background in econometrics, graph analytics, data engineering, and experience with IC datasets;

Qualifications

• Master's degree or PhD in a quantitative field required.
• 5+ years in quantitative economic modeling and econometrics.
• Experience with large-scale data processing and data pipelines.
• Experience with graph analytics and network modeling.
• Familiarity with IC mission environments and datasets.
• Strong written and oral communication for senior stakeholders.

Responsibilities

• Oversee design, evaluation, and application of quantitative economic models.
• Oversee integration of multi-source datasets into analytical pipelines.
• Serve as technical liaison between researchers, software teams, and IC stakeholders.
• Advise leadership on execution risks and data architecture scalability.
• Prepare documentation and executive briefs for progress and findings.

Skills

Quantitative modeling

Econometrics

Network data science

Graph analytics

Data engineering

Python/R

Executive communication

Education

Masters or PhD in a quantitative field

Tools

Graph databases

Network science frameworks

Python libraries

R libraries

Data pipelines

Job description

Complex Adaptive Systems

Clearance: TS with SCI eligibility. Active SAP eligibility preferred.

Location: Arlington, VA

Salary: Based on experience

The 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 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

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 environment 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

Responsibilities

• Oversee the design, evaluation, and application of quantitative economic models, network analysis frameworks, and graph-based data integration architectures
• Oversee the integration of complex, multi-source intelligence and economic datasets into scalable, operational analytical pipelines
• Serve as primary technical liaison between academic researchers, software engineering teams, and IC stakeholders to ensure tools align with operational requirements
• Adviseleadership on program execution risks, data architecture scalability, and capability transition strategy
• Prepare technical documentation, program roadmaps, and executive briefs to communicate program progress and analytical findings to senior decision-makers