Data Scientist - Computational Research, Statistics & Machine Learning

Job no: 503995 Work type: Regular Full-Time Location: Chicago - 300 E Randolph St Capability Area: Statistics and Data Science

NORC at the University of Chicago is seeking a qualified Data Scientist to join the Statistics and Data Science department and support a diverse range of research projects.

The Data Scientist I works collaboratively with statisticians, researchers, methodologists, software developers, and subject matter experts to develop statistical, data science, and computational 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. The position also provides opportunities to apply emerging technologies, including generative AI and large language models (LLMs), to research problems.

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 statistical and machine learning models, creating data products and applications, and evaluating AI approaches for research and operational use.

The ideal candidate possesses strong Python programming skills, experience building reproducible analytical workflows, and an interest in applying advanced computational, statistical, and AI methods to solve complex research and business problems.

Location
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This is a hybrid role based in either our Chicago Loop or downtown DC office, 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 Statistics and Data Science department implements state‑of‑the‑art statistical methods 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 Statistics and Data Science department also conducts its own research and is a leader in designing and implementing rigorous, efficient methods for sampling, weighting, and imputation for sample surveys and evaluation research.

The department provides expertise and leads NORC strategy on the use of a broad range of methods and techniques, including statistical modeling, machine learning methods, data linkage, statistical matching, data disclosure control, small area estimation, Bayesian analysis, assessing data quality, data visualization for analyzing and interpreting data, and developing approaches using artificial intelligence (AI) that support NORC’s research. The department collaborates with the departments throughout NORC, as well as leading its own projects.

• Apply statistical, computational, and machine learning methods to support survey research, evaluation studies, and other social science research initiatives
• Establish reproducible, quality‑assured analytic workflows; implement version control (Git), environment management, peer code review, automated testing, and validation checks.
• Develop robust data pipelines that integrate, transform, and analyze structured and unstructured data from multiple sources to support research and operational objectives.
• Design and implement data products, dashboards, applications, and automated tools that enable data‑driven decision…