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Computational Social Science Jobs in Virginia (NOW HIRING)

Koitecc Solutions

Senior AI Engineer

Alexandria, VA · On-site

$131 - $237/hr

Bachelor's, Master's, or equivalent graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.

Leidos

Business Data Analyst / Methodologist

Mclean, VA · On-site

$92K - $166K/yr

Bachelor's degree in Computer Science, Computational Social Science, Business Analytics, Data Analytics, or another field emphasizing advanced data analytics. * One of the following: * Bachelor ...

Leidos

Business Data Analyst / Methodologist

Mclean, VA · On-site

$92K - $166K/yr

Bachelor's degree in Computer Science, Computational Social Science, Business Analytics, Data Analytics, or another field emphasizing advanced data analytics. * One of the following: * Bachelor ...

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Computational Social Science information

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$40

$54

$73

How much do computational social science jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for computational social science in Virginia is $54.46, according to ZipRecruiter salary data. Most workers in this role earn between $46.49 and $72.93 per hour, depending on experience, location, and employer.

What is computational social science?

Computational social science is an interdisciplinary field that uses computational methods, such as data analysis, simulations, and modeling, to study social phenomena and human behavior. It combines tools from computer science, statistics, and social sciences to analyze large-scale social data, like social media activity, online interactions, or census records. This approach helps researchers uncover patterns and trends that would be difficult or impossible to detect using traditional social science methods alone.

What types of data sources and analytical methods are commonly used in computational social science roles?

In Computational Social Science positions, professionals typically work with large and diverse datasets, including social media feeds, digital communication records, surveys, and online behavioral data. Analytical methods often involve a mix of quantitative techniques such as network analysis, machine learning, natural language processing, and agent-based modeling. Collaborative projects may require integrating insights from computer science, sociology, and statistics, making interdisciplinary teamwork a frequent part of the role. Adapting to evolving data privacy guidelines and ensuring ethical data use are also important daily considerations.

What are the key skills and qualifications needed to thrive as a computational social scientist, and why are they important?

To thrive as a Computational Social Scientist, you need a solid background in social science research methods, statistics, and programming—often supported by an advanced degree in a relevant field. Familiarity with data analysis tools such as Python, R, machine learning libraries, and experience with large datasets or social network analysis software is typical. Strong analytical thinking, interdisciplinary collaboration, and effective communication skills help you interpret results and convey insights to diverse audiences. These competencies are crucial for generating impactful, data-driven insights into complex social phenomena and informing decision-making.

What is the difference between Computational Social Science vs Data Scientist?

AspectComputational Social ScienceData Scientist
Required CredentialsSocial science background, programming skillsStatistics, programming, domain knowledge
Work EnvironmentResearch institutions, academia, social research firmsTech companies, finance, healthcare
Employer & Industry UsageUniversities, government agencies, social research organizationsCorporations, startups, consulting firms
Common Search & ComparisonYesYes

Computational Social Science focuses on analyzing social phenomena using computational methods rooted in social science theories, often within academic or research settings. Data Scientists, however, apply statistical and machine learning techniques to large datasets across various industries. While both roles require programming skills, Computational Social Science emphasizes social theory and research, whereas Data Science centers on data analysis and business insights.

What can I do with a computational social science degree?

A computational social science degree prepares individuals for roles such as data analyst, social data scientist, or research analyst, where they analyze social data using statistical tools, programming languages like Python or R, and modeling techniques. Graduates can work in academia, government agencies, or private sector organizations focused on social research, policy analysis, or market research. Strong skills in data analysis, machine learning, and social theory are often essential for these positions.

What are popular job titles related to Computational Social Science jobs in Virginia?

For Computational Social Science jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Computational Social Science jobs in Virginia look for?

The top searched job categories for Computational Social Science jobs in Virginia are:

What cities in Virginia are hiring for Computational Social Science jobs?

Cities in Virginia with the most Computational Social Science job openings:

Computational Social Science jobs near you
Infographic showing various Computational Social Science job openings in Virginia as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $113,270 per year, or $54.5 per hour.

Senior AI Engineer

Koitecc Solutions

Alexandria, VA • On-site

$131 - $237/hr

Other

Medical, Retirement, PTO

Posted 7 days ago

Job description

Are you ready to thrive? Through training, teamwork, and exposure to challenging technical work, let Leidos show how to accelerate your career path.

Join Leidos’ all-star team supporting the Defense Intelligence Agency’s Enterprise Digital Modernization Accelerator initiative. This program is at the forefront of deploying enterprise-scale AI, data, and mission platform capabilities across cloud, edge, and classified environments. We are looking for creative, driven, and mission-focused professionals ready to take their career to the next level.

As a Senior AI Engineer, you will:
  • Support the development and operationalization of AI and agentic AI systems in production mission environments.
  • Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges and deliver innovative, production-ready algorithms and platforms.
  • Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics.
  • Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast-paced, engineering-centric environment.
  • Enjoy flexible work arrangements, including remote and on-site work in the National Capital Region (Rockville, MD and/or Alexandria, VA).
What You Bring:
  • Bachelor’s, Master’s, or equivalent graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.). Additional/Relevant experience may be substituted for a degree.
  • 12+ years of experience in data science, analytics, or quantitative intelligence analysis, developing analytics and AI/ML solutions (4+ years with a Master’s).
  • Active Top Secret clearance and eligibility for TS/SCI with Polygraph.
  • Demonstrated experience collaborating with hybrid teams to research, build, and deploy complex, user-friendly analytical platforms.
  • Track record of creative problem solving, active learning, and mission-focused outcomes.
  • Experience with the following:
    • AI/ML production engineering
    • LLMOps / MLOps
    • RAG architectures
    • AI orchestration frameworks
    • Kubernetes-based AI deployments
    • OpenAI-compatible APIs
    • Python development
    • GPU inference optimization
Preferred Qualifications:
  • Experience supporting military or intelligence community customers.
  • Familiarity with Azure/C2S, hardware platforms (CPUs, GPUs, FPGAs), and advanced analytical methodologies (social network analysis, supply chain analysis, NLP, classification algorithms, image processing).
  • Familiarity with the following technologies
    • LangGraph
    • Semantic Kernel
    • vLLM
    • Ollama
    • Ray
    • NVIDIA GPU ecosystems
    • Vector databases

#ASBA

#NMEC-Leidos

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

Original Posting:

June 25, 2026

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $131,300.00 - $237,350.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

About Leidos

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. Headquartered in Reston, Virginia, with 47,000 global employees, Leidos reported annual revenues of approximately $16.7 billion for the fiscal year ended January 3, 2025. For more information, visit www.Leidos.com.

Pay and Benefits

Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits.

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.

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