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Statistician - Health Systems Management-CHS

Job in Chicago, Cook County, Illinois, 60290, USA
Listing for: Rush University Medical Center
Full Time position
Listed on 2026-09-13
Job specializations:
  • Healthcare
    Clinical Research, Data Scientist, Medical Science
Salary/Wage Range or Industry Benchmark: 38 - 55 USD Hourly USD 38.00 55.00 HOUR
Job Description & How to Apply Below

Location:

Chicago, Illinois

Business Unit:
Rush Medical Center

Hospital:
Rush University Medical Center

Department:
Health Systems Management-CHS

Work Type:
Full Time (Total FTE between 0.9 and 1.0)

Shift: Shift 1

Work Schedule:

8 Hr (8:00:00 AM - 4:30:00 PM)

Rush offers exceptional rewards and benefits learn more at our Rush benefits page (https://www.rush.edu/rush-careers/employee-benefits).

Pay Range: $38.02 - $55.18 per hour

Rush salaries are determined by many factors including, but not limited to, education, job-related experience and skills, as well as internal equity and industry specific market data. The pay range for each role reflects Rush’s anticipated wage or salary reasonably expected to be offered for the position. Offers may vary depending on the circumstances of each case.

Summary

Under the general direction of the Statistician Manager, the Statistician 3 may work directly with study investigators and will be responsible for complex analyses of research data concerning topics in the biomedical sciences. Provides quantitative and analytic support to multiple research projects. The Statistician 3 acts as mentor and assists the Supervising Statistician or Statistician Manager in training Statisticians 1 and 2.

Exemplifies the Rush mission, vision, and values and acts in accordance with Rush policies and procedure

Other Information

Required

Job Qualifications:

  • Master’s degree in Biostatistics, Statistics or closely related field.
  • 7 years of experience performing statistical analysis of biomedical or related data.
  • Expertise in linear and logistic regression, longitudinal analysis and survival analysis methods.
  • Expert analytical skills.
  • Expertise with SAS or R/R-studio programming. Proficiency with Microsoft Office (Word, Excel, Power Point).
  • Clear and concise written and verbal communication skills.
  • Detail oriented and careful attention to accuracy.
  • Ability to function effectively within a team environment.
  • Ability to independently prioritize workload.
  • Ability to handle multiple projects, including quick projects with tight deadlines.
  • Some positions may require SQL/Database management skills.
Physical Demands Department Specific (RADC)
  • The Statistician 3 will working closely with data from Rush Alzheimer's Disease Center (RADC) research studies and with RADC investigators.
  • Follow RADC Statistics teams protocols and practices for SAS programs and R/Rstudio.
  • Participate in meetings of Biostatistics team and Center-wide activities (including Clinical Research Conference, Inside Highlights). In team meetings, describe any newly developed computed variables added to the Share Code. Communicate with Documentation team.
  • Assist in monitoring daily Share Code SAS runs. If a run fails, coordinate with other senior members of team and RADC Data Management staff to locate issues and rerun to generate tables.
  • Experience with analysis or conduct of longitudinal studies required.
Disclaimer

Disclaimer:
The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of duties, responsibilities or requirements.

Responsibilities
  • Independently compute new variables in output for specific requests, displaying stages by showing summaries of all records and by showing all data for one or more participants.
  • Independently develop, write, and run complex computer programs in SAS and R to
    1) utilize, summarize, and describe datasets, including frequencies, lists, and plots and
    2) perform statistical analyses of biomedical data, employing appropriate statistical methods, such as survival analyses, generalized linear modeling, non-parametric methods and graphical methods. Types of data analyzed include categorical, longitudinal, and…
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