Senior Applied Data Scientist

Protagonist is a company that specializes in data-driven communication strategies and innovative solutions. They are seeking a Senior Applied Data Scientist to design and implement data science solutions, leveraging advanced techniques to provide actionable insights and support client objectives.

Responsibilities:

• 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
• 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
• 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
• 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
• 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
• 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
• 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