Senior Computational Social Scientist

Protagonist•Washington, DC

1d•$82,216 - $129,885•Hybrid

About The Position

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-hatted role. You'll help lead our internal data efforts, stay hands-on with analysis and client delivery, and partner with the product team to shape Narrative Analytics™, the platform our analysts use every day. Whether you come from a social science research background, a product-and-analytics path, or a more technical track, what matters most is that you can take messy, real-world data and make it useful to our internal team and end customers.

Requirements

Must be eligible to work on US Government contracts.
A 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.
5+ years of relevant experience with a bachelor’s (or 3+ with an advanced degree), including at least 2 years focused on data science with a track record of real impact.
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.

Nice To Haves

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.

Responsibilities

Lead our data efforts
Guide internal data science work: shape the approach, hold quality high, and keep analysis reproducible and defensible.
Design and apply classification models, clustering, and other ML/AI approaches to surface insight from large, unstructured datasets.
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 clients with clarity and confidence.
Shape the product and work across streams
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.
Mentor junior analysts and interns and contribute technical sections to proposals and white papers.