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University of Pennsylvania

Posted Job Title Business Development Manager - Computational Social Science Lab - Penn Engineering Job Profile Title Manager Research Project B Summary The Computational Social Science Lab (CSSLab ...

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$50.5K

$111.3K

$137.5K

How much do computational social scientist jobs pay per year?

As of Jul 27, 2026, the average yearly pay for computational social scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What is a Computational Social Scientist job?

A Computational Social Scientist applies computational methods, data analysis, and social science theories to study human behavior, societal trends, and complex social systems. They use techniques like machine learning, network analysis, and simulations to analyze large-scale data from sources such as social media, surveys, and public records. Their work helps inform policy, business decisions, and academic research by uncovering patterns and insights in social data.

What are the key skills and qualifications needed to thrive in the Computational Social Scientist position, and why are they important?

To thrive as a Computational Social Scientist, you need a strong background in social science, statistical analysis, and computational methods, typically supported by an advanced degree such as a master's or Ph.D. in a related field. Proficiency with programming languages like Python or R, experience with data analysis platforms, and familiarity with database management systems are essential. Strong communication, problem-solving, and teamwork skills set candidates apart, especially when translating complex findings for diverse audiences. These competencies are critical for extracting meaningful insights from large datasets and effectively collaborating in interdisciplinary research environments.

What does a typical workday look like for a Computational Social Scientist?

A typical workday for a Computational Social Scientist often involves gathering and processing large datasets, running quantitative analyses or simulations, and interpreting the results to address social science questions. You might collaborate closely with other researchers, data analysts, and domain experts, as well as presenting findings to non-technical stakeholders. Responsibilities can also include writing research reports, developing new computational models, and staying current with methodological advancements. The pace and focus may vary depending on the stage of a project, but the role offers a dynamic blend of independent research and collaborative teamwork.

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What cities are hiring for Computational Social Scientist jobs? Cities with the most Computational Social Scientist job openings:
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Computational Social Scientist jobs near you
Infographic showing various Computational Social Scientist job openings in the United States as of July 2026, with employment types broken down into 67% Full Time, 31% Part Time, 1% Contract, and 1% Summer. Highlights an 66% Physical, 2% Hybrid, and 32% Remote job distribution, with an average salary of $111,343 per year, or $53.5 per hour.
Computational Social Scientist

Computational Social Scientist

Protagonist

Washington, DC

$70K - $102K/yr

Other

Posted 9 days ago

Job description

Washington, DC | Full-Time | Hybrid

Job Description

In this role, you'll apply data science and analytic methods directly to projects, turning large, often unstructured datasets into findings that teams and clients can act on. Our work lives at the intersection of data science and social science: we pair computational techniques with an understanding of the social, political, and information dynamics behind the data. This is a multi-faceted role. You'll support our internal data efforts, stay hands-on with analysis and client delivery, and work with the product team to help improve Narrative Analytics, the platform our analysts use every day. Whether your background is in social science research, product and analytics, or a more technical track, what matters most is that you can take messy, real-world data and make it useful for our team and our end customers.

Responsibilities
  • Contribute to our data efforts
    • Support internal data science work: apply sound methods, keep quality high, and keep analysis reproducible and defensible.
    • Build and apply classification models, clustering, and other ML/AI approaches to surface insight from large, unstructured datasets.
    • Help translate qualitative research questions into structured analytical workflows.
  • Build AI-powered analytical workflows
    • Design prompts, LLM chains, and agentic workflows that automate classification, thematic coding, entity extraction, and summarization at scale.
    • Build and evaluate repeatable analytical products with real quality controls and human-in-the-loop checks.
    • Experiment with emerging techniques (RAG, multi-step reasoning, tool-using agents) to extend what we can deliver.
  • Make data usable and clear
    • Handle complex cleaning, transformation, and wrangling so the data stays trustworthy.
    • Build dashboards and visualizations (Tableau, Superset, or similar) that make insight clear to clients and colleagues alike.
    • Turn findings into actionable recommendations and present them directly to both the internal team and customers with clarity and confidence.
  • Support the product and work across teams
    • Work hand in hand with the product team to shape Narrative Analytics around what users actually need, bringing the analyst's and client's perspective into product design.
    • Collaborate across analytics, product, and client teams so the work fits together and reaches the people who depend on it.
Requirements
  • Must be eligible to work on US Government contracts
  • A BS degree in a quantitative or analytical field (data science, computer science, statistics, computational social science, political science, economics, communications, or a related discipline), or equivalent hands-on experience.
  • 2+ years of relevant experience with a bachelor's or BS degree with relevant internship experience and a proven track record of leveraging analytics to drive significant business impact, or a 1+ years of relevant experience with a master's degree with strong, practical data analytics project experience or relevant internships.
  • Hands-on experience working with text-as-data: media, social media, or open-source text corpora.
  • Working proficiency in Python and/or R, plus solid SQL for pulling, transforming, and validating data.
  • Familiarity with core NLP and ML methods (text classification, topic modeling, sentiment and stance detection, embeddings, transformers) and with applying LLMs in real workflows (prompt engineering, structured outputs, integration).
  • The ability to explain technical work to non-technical audiences and to thrive in a fast-paced, collaborative team.
Ideal Candidates
  • Existing security clearance (SECRET or higher) a plus
  • Experience designing structured content analysis or analytical frameworks for text data.
  • Experience in information environment assessment, strategic communication analysis, or media landscape monitoring.
  • Experience shaping analytical tools or platforms around real user needs.
  • Experience with computational social science methods (network analysis, narrative framing, document similarity) that go beyond keyword search.
  • Experience translating social science research questions into scalable computational approaches.
Additional Information

If you're passionate about technology and making an impact, apply today! Protagonist is dedicated to fostering a welcoming and innovative environment where everyone's voice can make a difference.

Protagonist is an Equal Opportunity Employer. 

Salary Range: $70,000-$102,000 based on education and level of relevant experience.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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