Strategic Quantitative Analyst: Network Data & Economics

Everforth, Inc.; Arlington (VA); On-site; USD 150,000 - 195,000; Full time

Job summary

Everforth ECS seeks a Quantitative Analyst to work on-site in Arlington, VA, supporting DARPA program managers with complex adaptive system modelling, data-intensive analytics, and graph-based networks. The role requires integrating multi-source intelligence and economic data streams into scalable analytical pipelines.

The successful candidate will communicate analytical findings to senior decision-makers and advise on data architecture scalability and program risks, traveling up to 15% as

Qualifications

• Master’s degree or PhD in Economics, Data Science, Applied Mathematics, or related field.
• 5+ years of quantitative economic modeling, econometrics, and network data science experience.
• US citizen with active Top-Secret clearance and SCI eligibility.
• Experience with economic data and network analysis required.

Responsibilities

• Oversee design and evaluation of quantitative economic models and graph-based data integration architectures.
• Integrate multi-source intelligence and economic datasets into scalable analytical pipelines.
• Serve as liaison between researchers, software engineers, and IC stakeholders.
• Advise DARPA leadership on execution risks, data architecture scalability, and transition strategy.
• Prepare technical docs, roadmaps, and briefs for senior decision-makers.

Skills

Quantitative analysis

Econometric modeling

Network/data science

Python/R

Graph analytics

Education

Master’s degree in Economics

PhD in a quantitative field

Data Science degree

Tools

Python

R

Graph databases

Network analysis tools

Job description

Everforth ECS seeks a Quantitative Analyst to work on-site in Arlington, VA, supporting DARPA program managers with complex adaptive system modelling, data-intensive analytics, and graph-based networks. The role requires integrating multi-source intelligence and economic data streams into scalable analytical pipelines.

The successful candidate will communicate analytical findings to senior decision-makers and advise on data architecture scalability and program risks, traveling up to 15% as