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

NORC at the University of Chicago • Chicago, IL

5d • Hybrid

About The Position

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

Requirements

• Bachelor's degree in computational social science, data science, computer science or a related quantitative field with social science emphasis.
• At least 6 years of progressive relevant experience with large datasets, statistical analysis, predictive modeling, and data mining.
• Advanced proficiency in Python.
• Strong experience with SQL and relational databases.
• Familiarity with AI agents, RAG and workflow orchestration frameworks.
• 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.
• Qualified applicants must be eligible to work in the U.S.
• We regret that we are unable to offer visa sponsorship for this position.

Nice To Haves

• Additional expertise in large and small language models, and machine learning, in working in cloud environments (e.g., AWS, Azure, GCP), and with command-line workflows (e.g., in bash)
• Developing machine learning models, data pipelines, and AI-powered applications, as described above, to support social science research

Responsibilities

• 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.
• Develop reports, visualizations, dashboards, and presentations to communicate insights and recommendations.
• Partner with project leaders and stakeholders to support data-driven decisions and evaluate business impacts.
• Support the development of analytical tools and platforms to enhance organizational capabilities
• Collaborate on hypothesis development, experiment design, and feasibility analysis for new initiatives.
• Contribute to business development and proposal writing activities.
• Train, mentor, and provide technical guidance to staff on data processes, tools, and analytical methods.
• Perform other duties as assigned.

Benefits

• Generously subsidized health insurance, effective on the first day of employment
• Dental and vision insurance
• A defined contribution retirement program, along with a separate voluntary 403(b) retirement program
• Group life insurance, long-term and short-term disability insurance
• Generous paid time off
• Holidays
• Paid parental leave
• Bereavement leave
• Tuition assistance
• An Employee Assistance Program (EAP)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level