Data Analyst I or II - Statistics and Data Science research support

NORC at the University of Chicago is seeking a qualified Data Analyst I or II (we are open to hiring at either level) to join the Statistics and Data Science department and support a diverse range of research projects. At NORC, Data Analysts are early career team members who train and work with our Statisticians and Data Scientists to perform tasks such as data processing, quality assurance, analysis, and dissemination.

As part of their data processing responsibilities, Data Analysts import, clean, standardize, transform, and validate data sets. They also research and document data procedures and support the investigation of data problems. They may identify, analyze, and interpret trends or patterns in data sets, support modeling efforts, and help prepare data presentations and reports, including developing charts, graphs, and tables. In addition, the Data Analyst may assist in data collection and harmonization from primary or secondary data sources (e.g., administrative records, commercial data, social media data), preparing data files for delivery, and the maintenance of databases, data systems, and their relevant metadata/dictionaries. The Data Analyst is expected to work collaboratively in a team environment.

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

Location: 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.

We welcome interest from future graduates; however, this position requires a completed Bachelor's degree. If you are still pursuing your degree, please consider applying once your graduation requirements have been met.

The Statistics and Data Science (SDS) department provides the scientific foundation required to advance NORC’s project portfolio. SDS delivers rigorous, innovative, and fit-for-purpose solutions along the project lifecycle. The department provides leadership for NORC’s approach on a broad range of approaches for study design and the analysis of primary and secondary data. SDS expertise includes artificial intelligence and machine learning; Bayesian analysis; causal inference; disclosure avoidance; imputation; data linkage and statistical matching for combining multiple data sources; data quality assessment; efficient and reproducible workflow development; privacy-preserving methods; small area estimation; statistical methods for survey sampling, weighting, estimation, and inference; and visualization.

The SDS department works closely with research, technology, and operational teams across NORC to ensure that statistical excellence and innovation remain central to the organization’s work. Many of NORC’s projects and proposals are led by substantive research departments that require significant contributions from SDS staff. SDS works closely with highly collaborative groups across the organization to ensure success through cross-departmental partnerships. To further capture the innovative spirit of NORC, SDS also leads projects that target departmental focus areas. Examples of recent project topics involving SDS staff include survey design, weighting, and analysis; AI for enhancing data quality, standardization, and integration; enhancing traffic safety data; linkage of health administrative data and surveys; and testing data visualization approaches for effective communication.

The pay range for this position is $62,000-$73,000.

This position is classified as regular. Regular staff are eligible for NORC’s comprehensive benefits program. Benefits include, but are not limited to:  

NORC is committed to equity and transparency in its pay practices. We publish salary ranges and benefit information for every job. The listed hiring range reflects what we, in good faith, expect to pay at the time of posting, though actual compensation may vary and may be adjusted over time. A candidate’s placement within the range depends on factors such as competencies, education, qualifications, experience, skills, performance, and organizational needs.