Technical Quantitative Analyst

Systems Planning and Analysis, Inc. (SPA) delivers high-impact, technical solutions to complex national security issues. With over 50 years of business expertise and consistent growth, we are known for continuous innovation for our government customers, in both the US and abroad. Our exceptionally talented team is highly collaborative in spirit and practice, producing Results that Matter. Come work with the best! We offer opportunity, unique challenges, and clear-sighted commitment to the mission. SPA: Objective. Responsive. Trusted.

The Joint, Office of the Secretary of Defense, Interagency Division provides expert support services to a range of customers spanning across the Department of Defense, Federal Civilian, and international markets. JOID provides a diverse portfolio of analytical and programmatic capabilities to help our customers make informed decisions on their most challenging issues.

SPA provides critical decision support to enabling and executing a strategy of technological superiority and enabling the delivery and sustainment of secure, resilient, and preeminent capabilities to the warfighter quickly and cost effectively. Our team of experienced military, technical, and operations research analysts is skilled in evaluating military problems, identifying the driving factors, devising innovative approaches, collecting applicable data, developing necessary software tools, and performing thorough and timely assessments to inform technology and acquisition governance decisions to ensure U.S. military forces retain military superiority in the future.

We have an immediate need for a Quantitative Analyst SETA to provide onsite support out of Arlington, VA.

The successful candidate will serve as a Quantitative Analyst SETA supporting DARPA 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. The candidate will serve as the primary technical liaison between academic researchers, software engineering teams, and IC stakeholders to ensure tools align with operational requirements. Will also advise DARPA leadership on program execution risks, data architecture scalability, and capability transition strategy.

Required:

• Master's degree or PhD in Economics, Data Science, Applied Mathematics, or a related quantitative field

• Active TS/SCI clearance

• 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

• Able to work fully onsite based on client needs
• Travel to support program operations up to 15% duty factor

Desired:

• 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

• 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
• 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