Data Analyst I or II - Statistics and Data Science research support
University of Chicago
Summary
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.
Job description
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.
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.
Required Skills
- Bachelor’s degree in statistics, data science, computer science, or an equivalent field.
- 0-2 years’ relevant experience (internships included).
- Statistical programming in multiple packages and databases, including Python (required)
- Familiarity working with large data sets, conducting statistical and quantitative modeling with strong programming.
- Strong foundation in areas of analytic methods, data engineering, machine learning, and scientific methods of inquiry.
- Experience with data management, data reduction techniques and data visualization.
- Working knowledge of different types of data that can be sourced whether from administrative data, surveys, social media, or sensor data.
- Strong skills in problem solving and quantitative analysis are required, including a willingness to understand deviations and ask questions about data issues.
- Able to organize and prioritize work assignments to meet project needs.
- Strong communication, writing and data storytelling skills.
- Enthusiasm for teamwork and collaboration across disciplinary boundaries.
Preferred Skills
- Experience working with SAS, Tableau, Hadoop, Hive, Databricks, MapReduce, and/or other large data systems
- 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)
- Experience with JavaScript programming.
Requirements
- Bachelor’s degree in statistics, data science, computer science, or an equivalent field.
- 0-2 years’ relevant experience (internships included).
- Statistical programming in multiple packages and databases, including Python (required)
- Familiarity working with large data sets, conducting statistical and quantitative modeling with strong programming.
- Strong foundation in areas of analytic methods, data engineering, machine learning, and scientific methods of inquiry.
- Experience with data management, data reduction techniques and data visualization.
- Working knowledge of different types of data that can be sourced whether from administrative data, surveys, social media, or sensor data.
- Strong skills in problem solving and quantitative analysis are required, including a willingness to understand deviations and ask questions about data issues.
- Able to organize and prioritize work assignments to meet project needs.
- Strong communication, writing and data storytelling skills.
- Enthusiasm for teamwork and collaboration across disciplinary boundaries.
Benefits
- Health Insurance
- Dental & Vision Insurance
- Defined Contribution Retirement
- 403(b) Retirement Program
- Group Life Insurance
- Long-Term Disability Insurance
- Short-Term Disability Insurance
- Paid Time Off
- Paid Holidays
- Paid Parental Leave
- Bereavement Leave
- Tuition Assistance
- Employee Assistance Program
Company overview
The University of Chicago is a world-renowned private research university founded in 1890 and located in Chicago's Hyde Park neighborhood. As a premier academic institution, it operates one of the most comprehensive biomedical research enterprises in the United States through its Biological Sciences Division, which includes over 1,100 faculty members across 10 basic science and 14 clinical departments. The university manages extensive research infrastructure including the University of Chicago Medicine Comprehensive Cancer Center, multiple specialized research institutes, and maintains affiliations with Argonne National Laboratory and Fermi National Accelerator Laboratory. With research funding exceeding $450 million annually and more than 3,300 patents filed since 1987, the institution is a global leader in scientific discovery and innovation. The Biological Sciences Division alone supports over 500 research-active faculty who secure an average of $588,000 in NIH funding per principal investigator, focusing on areas including cancer biology, immunology, microbiology, molecular metabolism, neuroscience, and evolutionary biology. The university's commitment to interdisciplinary research and its unique position as manager of national laboratories creates unparalleled opportunities for translational research and scientific advancement.