Data Analyst II - Statistics and Data Science - Hybrid Chicago Loop Office

NORC at the University of Chicago is seeking a qualified Data Analyst II 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. For this role, we are looking for someone proficient in SAS, R, and Python.

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., 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. RESPONSIBILITIES:

• Collaborate with statisticians, data scientists, technology experts, and subject matter experts to implement and improve data management and analysis activities.
• Develop programs and scripts for data cleaning, integration, transformation, and harmonization, as well as data quality checks and validation
• Support and enhance applications and databases already built for various research needs and produce data documentation and dictionaries.
• Create data dashboards and visualizations, including preparing charts, graphs, and tables for reports and presentations.
• Perform various types of data analysis and modeling, often involving multiple data sets.
• Contribute to documentation, reports, and presentations through writing sections, creating basic analytic summaries, and developing tables and graphics.
• Apply AI tools to help improve efficiency.
• Perform other duties as assigned.

• Bachelor's degree in one of the following fields: statistics, math, data science, computer science, or computational social science or related field required.
• Proficiency with data management, quantitative analysis and modeling, data reduction techniques and data visualization.
• At least 2 years' experience in positions of increasing responsibility, preferably working with large data sets, and conducting statistical and quantitative modeling, statistical/analytic programming[SP1] , and data mining
• Strong foundation in areas of statistics, mathematics, and data science.
• Coding skills in SAS, R, and Python required.
• Additional expertise in areas of machine learning such as natural language processing and supervised/unsupervised modelling preferred.
• Experience using AI tools and methods (e.g., prompt engineering, agentic AI, model evaluation) is preferred.
• Strong skills in problem solving and quantitative analysis are required. Able to organize and prioritize work assignments to meet project needs.
• Outstanding interpersonal and critical reasoning skills.
• Proficiency with MS Office software.
• Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position.

life insurance, vision insurance, parental leave, paid time off, tuition assistance, 403(b), The pay range for this position is $72,000 - $88,000.

This position is classified as regular. Regular staff are eligible for NORC's comprehensive benefits program. Benefits include, but are not limited to: * 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 * Benefits that promote work/life balance, including generous paid time off, holidays; paid parental leave, bereavement leave, tuition assistance, and an Employee Assistance Program (EAP).

For over 80 years, NORC has evolved in many ways, moving the needle with research methods, technical applications and groundbreaking research findings. But our tradition of excellence, passion for innovation, and commitment to collegiality have remained constant components of who we are as a brand, and who each of us is as a member of the NORC team. With world-class benefits, a business casual environment, and an emphasis on continuous learning, NORC is a place where people join for the stellar research and analysis work for which we're known, and stay for the relationships they form with their colleagues who take pride in the impact their work is making on a global scale. EEO STATEMENT