Data Scientist supporting social science research, analytics, and AI initiatives

Job Summary

NORC at the University of Chicago is seeking a qualified Data Scientist I to join the Methodology and Quantitative Social Sciences department and support innovative research, analytics, and AI initiatives.

The Data Scientist I works collaboratively with methodologists, researchers, statisticians, software developers, and subject matter experts to develop data science and artificial intelligence solutions that improve research, operational efficiency, and decision-making. This role combines strong foundations in data management, statistical modeling, machine learning, and computational social science with emerging capabilities in generative AI and large language models (LLMs).

The Data Scientist I will contribute to projects involving structured and unstructured data, survey data, administrative records, commercial data, text data, and other novel data sources. Responsibilities may include developing analytical workflows, building machine learning models, creating AI-powered applications, fine-tuning foundation models, implementing retrieval-augmented generation (RAG) systems, and supporting deployment of AI solutions in secure cloud environments.

The ideal candidate possesses strong Python programming skills, experience building reproducible analytical workflows, and a demonstrated interest in applying modern AI technologies to solve complex research and business problems.

Location
:
This is a hybrid role based in our Washington, DC and Chicago downtown offices, with a minimum of six days per month in the office.

Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position.

The Methodology and Quantitative Social Sciences department implements state-of-the-art methodologies and develops innovations to deliver reliable data and rigorous analysis to guide critical programmatic, business and policy decisions for NORC clients. The department provides leadership throughout the project lifecycle on study design, data collection, assessment of data quality, quantitative analysis, and dissemination of results. The Methodological and Quantitative Social Sciences department also conducts its own research and is a leader in designing and implementing rigorous, efficient methods for gathering, evaluating, and analyzing data from primary and secondary sources.

The department provides expertise and leads NORC strategy on the use of a broad range of methods and techniques, including research and experimental design, recruitment and retention, instrument design and testing, assessing data quality, evaluating measurement properties of new measures, causal inference methods, machine learning, analysis of clustered data, data visualization, use of novel data sources and technologies to improve data gathering, and building AI solutions that support NORC's research.

The department collaborates with the Statistics and Data Science Department on areas of synergy and intersection and with all NORC subject matter departments, in addition to leading its own projects.

Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position.

• Collaborate with methodologists and subject matter experts to design, develop, evaluate, and deploy AI-enabled applications that support research and operational objectives.
• Fine-tune, adapt, or customize machine learning and language models for domain-specific tasks.
• Build and evaluate retrieval-augmented generation (RAG) solutions using vector databases and semantic search techniques for data and analysis projects in NORC's research focus areas.
• Develop prompt engineering strategies and evaluation frameworks for generative AI systems.
• Implement model monitoring, testing, validation, and performance optimization processes.
• Apply natural language processing techniques for text classification, information extraction, summarization, and content analysis.
• Support experimentation with AI agents, tool calling, and workflow automation.
• Perform other duties as assigned.

• Bachelor's degree in computational social science, data science, computer science or a related quantitative field with social science emphasis.
• At least 4 years of relevant experience (graduate research, internships, and applied professional experience may be considered).
• Advanced proficiency in Python.
• Strong experience with SQL and relational databases.
• Experience developing software, data pipelines, or analytical applications.
• Experience conducting statistical analysis and machine learning using real-world datasets.
• Knowledge of supervised and unsupervised machine learning methods.
• Experience working with Git and collaborative development workflows.
• Strong problem-solving and analytical skills.
• Excellent communication and technical writing skills.
• Ability to explain technical concepts to diverse audiences.

Preferred

Skills:

• Familiarity with AI agents and workflow orchestration…