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Applied Social Science Jobs (NOW HIRING)

Senior Researcher

Saint Paul, MN · Hybrid

$88K - $143K/yr

AND experience (including applied social science research; advanced data analysis and statistical modeling; information design, data visualization and/or technical communications or content strategy ...

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Applied Social Science information

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$31.5K

$50.6K

$68K

How much do applied social science jobs pay per year?

As of Jun 19, 2026, the average yearly pay for applied social science in the United States is $50,609.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,500.00 and $53,000.00 per year, depending on experience, location, and employer.

What types of projects or problems do professionals in Applied Social Science typically work on?

Professionals in Applied Social Science often work on projects that address real-world issues such as improving workplace culture, evaluating the effectiveness of social programs, or conducting community needs assessments. Their daily responsibilities may include designing and implementing surveys, analyzing qualitative and quantitative data, and preparing reports or recommendations for clients or organizations. Collaboration is common, as these roles frequently involve working with multidisciplinary teams, stakeholders, and sometimes members of the public. This variety of work allows for substantial impact on policy decisions and organizational strategies, making the role both dynamic and rewarding.

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

To thrive in an Applied Social Science role, you need a background in social science research methods, data analysis, and a relevant degree such as sociology, psychology, or anthropology. Familiarity with statistical software like SPSS, Qualtrics, or NVivo, and sometimes professional research certifications, is often required. Strong analytical thinking, effective communication, and teamwork are essential soft skills that enhance performance in this field. These abilities are crucial for delivering actionable insights, informing policy or program development, and collaborating with diverse stakeholders.

What jobs can I get with applied science?

Applied social science graduates can pursue careers in areas such as social research, community development, policy analysis, human services, and public relations. These roles often require strong communication, research skills, and knowledge of social theories, with opportunities in government agencies, non-profit organizations, and consulting firms.

What are the three applied social sciences careers?

Applied social science careers include roles such as social researcher, community development specialist, and policy analyst. These positions often require skills in data analysis, research methods, and understanding social systems, and they are found in government agencies, non-profit organizations, and consulting firms.

What careers with a social science degree?

A social science degree prepares individuals for careers such as social researcher, community service manager, policy analyst, human resources specialist, and market researcher. These roles often require strong analytical, communication, and research skills, and may involve working in government agencies, non-profits, or private companies.

What is an Applied Social Science job?

An Applied Social Science job involves using principles from disciplines like sociology, psychology, and economics to address real-world problems. Professionals in this field work in areas such as social research, policy analysis, community development, and human services. Their goal is to apply theoretical knowledge to create practical solutions that improve individual and societal well-being. Jobs may be found in government agencies, nonprofits, education, healthcare, or corporate settings where social insight is valuable.

What jobs pay $10,000 a month without a degree?

In applied social science, roles such as freelance consultants, social media managers, or sales professionals can reach $10,000 monthly through experience, client base, or commissions. These jobs often require strong communication skills, networking, and self-motivation, and may involve remote work or flexible schedules.
More about Applied Social Science jobs
What cities are hiring for Applied Social Science jobs? Cities with the most Applied Social Science job openings:
What states have the most Applied Social Science jobs? States with the most job openings for Applied Social Science jobs include:
Infographic showing various Applied Social Science job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 42% Full Time, 45% Part Time, 1% Temporary, 9% Contract, and 1% Nights. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $50,609 per year, or $24.3 per hour.
Senior Computational Social Scientist (1099)

Senior Computational Social Scientist (1099)

Protagonist

Washington, DC

Other

Posted 20 days ago


Job description

Washington, DC | This is a temporary position with an initial period of 90 days. Successful performance during this period may lead to a permanent role | Hybrid

Job Description

*Note that this a temporary subcontract position--outstanding performance may lead to full-time consideration; We are also recruiting for a full-time Senior Computational Social Scientist based in Washington, DC-please visit our careers page for details and to apply*

You are a data science professional with a passion for applying best-in-class data science methodologies to solve real-world challenges. With extensive experience in designing, building, and deploying sophisticated data solutions, you excel at transforming raw, unstructured data into structured analytical products that inform decision-making. You lead internal data efforts-from rigorous data cleaning to impactful data visualizations-and effectively present data findings to clients. You are an analyst at heart, possessing the curiosity and acumen to know when to ask the right questions of data and what questions will drive meaningful insights. You understand that the most powerful analytical work bridges computational methods with deep understanding of the social, political, and information dynamics that generate the data in the first place.

Responsibilities
  • Applied Data Science & Solution Implementation:
    • Design, develop, and deploy scalable, production-ready data science solutions that align with business and project goals.
    • Leverage AI, machine learning, and advanced statistical techniques to extract insights from complex, large-scale, or unstructured datasets.
    • Apply techniques such as classification models, clustering algorithms, and other AI methods to drive discovery and inform decision-making.
    • Design and implement codebook-driven analytical frameworks that translate qualitative research questions into reproducible computational workflows.
    • Build and iterate on applied models tailored to project and client needs.
    • Translate analytical findings into actionable recommendations, delivering measurable impact for both internal and external stakeholders.
    • Provide direct support to the Engineering team as needed to implement solutions.
  • Applied AI & Automated Workflows:
    • Design and refine prompts, LLM chains, and agentic AI workflows that automate analytical tasks such as content classification, thematic coding, entity extraction, and structured summarization at scale.
    • Build and evaluate automated analytical products and pipelines that integrate large language models into repeatable, production-grade workflows with appropriate quality controls.
    • Experiment with emerging AI techniques-including retrieval-augmented generation (RAG), multi-step reasoning chains, and tool-using agents-to extend the company's analytical capabilities and accelerate delivery.
  • Data Preparation, Cleaning & Visualization:
    • Write and maintain efficient, reproducible data pipelines using Python, R, SQL, or similar tools.
    • Perform complex data cleaning, transformation, and wrangling to ensure high-quality analytical output.
    • Create compelling dashboards and visualizations using Tableau, Superset, or other tools to communicate insights to both clients and internal teams.
  • Analytical Framework Design & Research:
    • Contribute to the design, refinement, and validation of analytical frameworks that structure how the company assesses complex information environments.
    • Bridge social science theory and computational practice, ensuring that analytical products are methodologically sound and defensible.
  • Cross-Team Collaboration, Client Engagement & Business Development:
    • Collaborate with engineering and product teams to build integrated analytical solutions supporting the company's Narrative Analytics approach.
    • Partner closely with engineering to translate data science requirements into scalable, production-ready tools and pipelines.
    • Contribute to data architecture decisions, tool selection, and infrastructure development to ensure alignment between analytics and engineering capabilities.
    • Present data findings to clients with clear communication and actionable recommendations.
    • Contribute to business development efforts requiring data science expertise, including writing technical sections of proposals, white papers, and concept notes.
  • Leadership & Internal Data Initiatives:
    • Lead improvements to internal data science workflows, methodologies, and quality assurance processes.
    • Mentor junior team members and interns, promote technical upskilling, and foster open discussion of best practices and emerging techniques in NLP, ML, and computational social science.
    • Contribute to the development and maintenance of shared analytical assets such as codebooks, scoring frameworks, and model evaluation protocols.
  • Collaboration & Professional Conduct:
    • Demonstrate ownership, professionalism, and timely follow-through in all responsibilities and communications.
    • Thrive in a fast-paced, dynamic environment by adapting to shifting priorities and proactively identifying opportunities to improve processes and analytic contributions.
    • Communicate technical insights clearly and translate complex data science needs into actionable guidance for both technical and cross-functional teams.
    • Foster collaboration across teams with openness to feedback, respect for diverse expertise, and a commitment to continuous learning.
Requirements
  • Eligibility & Security:
    • Must be eligible to work on US Government contracts.
    • Existing security clearance (SECRET or higher) is a plus.
    • Bachelor's or advanced degree (master's or Ph.D.) in Data Science, Computer Science, Statistics, Mathematics, Computational Social Science, or a related field.
    • Experience requirements: Bachelor's degree and 5+ years of relevant experience (or advanced degree and 3+ years of experience).
  • Professional Experience:
    • 2+ years of proven experience in data science, with a strong track record of driving significant business impact through applied analytics.
    • Demonstrated experience working with text-as-data, including media, social media, or open-source text corpora.
  • Technical Expertise:
    • Proficiency in Python and/or R for data analysis, modeling, and machine learning.
    • Strong SQL skills for data extraction, transformation, and integrity assurance.
    • Experience with NLP techniques including text classification, topic modeling, sentiment analysis, embedding-based methods, and transformer architectures.
    • Experience with statistical and predictive modeling techniques such as support vector machines, random forests, and classification models.
    • Demonstrated familiarity with the application and use of large language models (LLMs), including prompt engineering, structured output design, and integrating language models into applied analytical workflows.
    • Familiarity with modern data tools and data lake architectures supporting scalable, data-driven solutions.
    • Skilled in building insightful visualizations using tools like Tableau, Superset, Power BI, or Looker.
  • Interpersonal Skills:
    • Exceptional ability to communicate complex technical concepts to both technical and non-technical audiences.
    • Effective working both independently and in cross-functional teams, with a collaborative and solution-oriented mindset.
Ideal Candidates

The strongest candidates will bring experience designing or implementing structured content analysis frameworks or structured analytical methodologies for text data, along with familiarity with information environment assessment, strategic communication analysis, or media landscape monitoring. They will have built ML pipelines that include human-in-the-loop validation, analyst review steps, or active learning workflows, and will have exposure to computational social science research methods such as causal inference, network analysis, or computational text analysis beyond keyword search-including techniques like stance detection, narrative framing, and document similarity. Experience designing LLM chains, agentic AI systems, or automated analytical products that move beyond one-off prompting into repeatable, quality-controlled workflows is highly valued. Above all, ideal candidates will have a track record of 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: This is an hourly based short-term contracted position; hourly rate commensurate with 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.