Computational Analytics Researcher, National Security Data and Policy Institute

Virginia Jobs

$110K — $120K *
Education, Government & Non-Profit
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree required; MS or PhD in related quantitative discipline preferred.
  • 5+ years relevant experience in software application development and machine learning.
  • Proficient in Python and modern software engineering practices.
  • Experience in managing and analyzing large datasets.
  • Ability to obtain a security clearance.

Responsibilities

  • Lead and conduct sponsored research in computational analytics and AI.
  • Develop innovative analytical methodologies with machine learning and related techniques.
  • Design and evaluate software prototypes and decision-support tools.
  • Integrate diverse data sources to support analytic workflows.
  • Develop scalable data processing pipelines for government research.
  • Evaluate emerging technologies for potential integration into research.
  • Document findings through reports and publications.

Benefits

  • Collaborative research environment with access to faculty and industry partners.
  • Opportunities for professional development and interdisciplinary collaboration.
  • Engagement with government sponsors and influence on technical research agenda.
  • Participation in technical meetings, workshops, and conferences.
Full Job Description
The National Security Data and Policy Institute (NSDPI) at the University of Virginia seeks a Computational Analytics Researcher to conduct and lead applied research supporting the U.S. national security community. This position focuses on developing advanced computational methods, artificial intelligence, machine learning, and data science capabilities to address complex national security challenges. The successful candidate will work within interdisciplinary teams to develop innovative analytic solutions, publish research, engage with government sponsors, and transition research into operational capabilities.

The Computational Analytics Researcher will contribute to a growing portfolio of sponsored research involving artificial intelligence, data science, geospatial analytics, emerging technologies, supply chain security, critical infrastructure resilience, and strategic competition. This position offers opportunities to collaborate with faculty, government agencies, industry partners, and students while helping shape the Institute's technical research agenda.

Responsibilities:

Research and Technical Leadership
  • Lead and conduct sponsored research in computational analytics, artificial intelligence, and data science.
  • Develop innovative analytical methodologies using machine learning, large language models, statistical modeling, optimization, network science, and related computational techniques.
  • Design, implement, and evaluate software prototypes and decision-support tools.
  • Integrate structured, semi-structured, and unstructured data from multiple sources to support complex analytic workflows.
  • Develop scalable data processing pipelines and analytical frameworks for government-sponsored research.
  • Evaluate emerging technologies and identify opportunities to incorporate new computational methods into research programs.
  • Document research findings through technical reports, peer-reviewed publications, conference presentations, and sponsor briefings.


Program Development and Sponsor Engagement
  • Support the development of new research initiatives aligned with Institute priorities.
  • Participate in proposal development, technical volume preparation, and research planning.
  • Engage with federal sponsors, industry partners, and academic collaborators to identify new research opportunities.
  • Assist with project planning, milestone tracking, and technical execution across multiple research efforts.


Interdisciplinary Research Collaboration
  • Collaborate with faculty, research staff, software developers, and subject matter experts across multiple disciplines.
  • Foster interdisciplinary collaboration across technical and policy-focused research teams.
  • Support professional development activities and contribute to a collaborative research environment.


Service and Outreach
  • Represent NSDPI at technical meetings, workshops, conferences, and sponsor engagements.
  • Support Institute seminars, technical exchanges, and collaborative research initiatives.
  • Contribute to strategic planning and other Institute activities as assigned.

Minimum Qualifications
  • Education: Bachelor's degree required, MS or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Applied Mathematics, Statistics, Computational Social Science, Engineering, or a closely related quantitative discipline strongly preferred.
  • Experience: 5+ years relevant professional experience required. Relevant experience includes developing software applications using Python and modern software engineering practices, experience applying machine learning or artificial intelligence techniques to complex analytical problems, experience managing and analyzing large datasets.
  • Ability to obtain a security clearance.


The ideal candidate will have strong written and verbal communication skills, including experience preparing technical reports and presenting research findings and demonstrated ability to work both independently and collaboratively within multidisciplinary teams.

Preferred Qualifications

Preference will be given to candidates with experience in one or more of the following

areas:
  • Large language models and foundation models
  • Retrieval-augmented generation (RAG)
  • Agentic AI systems
  • Knowledge graphs
  • Reinforcement learning
  • Natural language processing
  • Computer vision
  • Time-series forecasting
  • Network science
  • Geospatial analytics
  • High-performance computing
  • Cloud computing environments (AWS, Azure, Google Cloud)
  • GPU programming and distributed computing
  • Data engineering and scalable analytics
  • Supply chain analytics
  • Critical infrastructure analysis


Physical Demands

This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling to sponsor locations, conferences, workshops, and technical meetings.

The hiring range is $110,000 - $120,000, commensurate with education and experience.

This is an exempt-level, benefited position. Learn more about UVA benefits .

This is a restricted position, which is dependent on funding and is contingent upon funding availability.

This position has a term of one year with possibility of renewal dependent on department need, performance, and funding.

This position is based in Charlottesville, VA, and must be performed fully on-site. The position is located within the National Security Data and Policy Institute at the University of Virginia. Work is performed in a collaborative research environment involving faculty, staff, students, government agencies, and industry partners. Depending on project requirements, access to secure government facilities may be required.

To learn more about UVA and in the Charlottesville area, visit UVA Life and Embark CVA .

Application review will begin afterAugust 16, 2026.

How to Apply

Please apply online , by searching for requisition number R[redacted]. Complete an application with the following documents:
  • Curriculum Vitae or Resume
  • Cover Letter
  • Statement of Research Interests (optional but encouraged)


Upload all materials into the resume submission field. You can submit multiple documents into this one field or combine them into one PDF. Applications without all required documents will not receive full consideration.

Internal applicants: Search and apply for jobs on the UVA Internal Careers website .

Reference checks will be completed by UVA's third-party partner, SkillSurvey, during the final phase of the interview. Five references will be requested, with at least three responses required.

For questions about the application process, please contact Jessica Russo, Senior Recruiter, [redacted].

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