Research Data Scientist

Barone Consulting LLC; Arlington (VA); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Barone Consulting LLC is seeking a seasoned professional to support a cutting-edge computing program from inception to execution. The role involves evaluating progress, advising the program manager, and preparing briefing materials.

You will help address Heilmeier criteria, perform literature reviews, and coordinate program reviews. Ideal candidates have advanced expertise in quantitative economic modeling, econometrics, and network data science applied to complex adaptive systems, plus

Qualifications

• Master’s degree or PhD in Economics, Data Science, Applied Mathematics, or related quantitative field.
• 5+ years in quantitative economic modeling, econometrics, and network data science/data engineering for complex adaptive systems.
• Experience with large-scale data processing and multi-source data pipelines.
• Proficiency with graph analytics and related tools (Python/R, graph databases).
• Familiarity with IC mission environments and intelligence-derived datasets.

Responsibilities

• Oversee design and evaluation of quantitative economic models and network analysis frameworks.
• Integrate multi-source datasets into scalable analytical pipelines.
• Conduct literature reviews and prepare briefing materials for program approvals.
• Support new program development addressing Heilmeier criteria.
• Lead program reviews, assessments, and risk management activities.
• Prepare reports and presentations for senior defense stakeholders.

Skills

Quant econ modeling

Econometrics

Network data science

Data engineering

Communication skills

Education

Master’s or PhD in Economics/Data Science/Applied Mathematics

Tools

Python/R

Graph databases

Network analytics tools

Job description

The successful candidate will support the program manager (PM) on managing an innovative computing program from start to finish. In this capacity, the candidate will evaluate the technical progress of performers, provide feedback to the PM and to the performers, advise the PM on overall program planning, prepare summary briefing materials for the PM, and coordinate program reviews and meetings. The candidate will also support new program development by helping to address the Heilmeier criteria, performing background literature reviews and research, and preparing briefings and documentation.

Expert knowledge and experience in the following areas are desired quantitative economic modeling, advanced econometrics, and network data science/data engineering applied to complex adaptive systems.

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
• Analysis of emerging science and technology R&D opportunities through literature review; outreach to the research community; summarizing, analyzing, and visualizing data in spreadsheet and graphical forms
• Generating briefing materials and agency documents required for new program approval
• Program management at all stages over the program lifecycle including BAA drafting; feedback on proposals; interactions with proposers and performers; meeting organization and participation; transition partner and industry partner engagement
• Lead periodic performer assessments to analyze findings, assess technical and schedule risks; develop management strategies; communicate findings to program manager
• Technical evaluations and guidance on reports, briefings, and other performer communications
• Presentation and report preparation
• Program administration, including development of technical analyses, identification of technology gaps, technical risk management, project cost estimation, technology transfer efforts, as well as supporting technical reviews
• Attending and organizing program reviews/site visits/field tests

Required capabilities and characteristics:

• 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

Desired capabilities and characteristics:

• 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