Sr. Data Analyst, Health Services

Location: Chicago, IL

Remote Type: Hybrid

Time Type: Full time

Job Description

Department

BSD SUR - Research Services

About the Department

Operating since 1927 on a strong foundation of multidisciplinary clinical and academic excellence, the University of Chicago Department of Surgery's mission is to meet the most challenging and complex health problems on both a local and global scale.

Many of our faculty members are known for their contributions to the advancement of groundbreaking surgical procedures and techniques, including minimally invasive surgery. In addition to our department's clinical work, our scientists pursue a diverse range of basic, translational, and clinical research projects, including studies on the gut microbiome, tissue bioengineering, stem cell research, cancer, and immunotolerance.

This ongoing work and achievement would not be possible without the cohesive effort and commitment of the faculty and staff. We are looking for high energy, collaborative individuals who share our commitment to improving the health of patients in the community and beyond.

Job Summary

The job provides professional support and solves problems in collecting, organizing, and analyzing information from the University's various internal data systems as well as from external sources. The job performs data analysis assignments related to data manipulation, statistical applications, programming, analysis and modeling in order to support the research efforts of faculty members focused on surgical health services and implementation outcomes research.

Responsibilities

• Conducts statistical analysis to support surgical outcomes and health services research.

• Manages and analyzes large national datasets, including clinical datasets (e.g., NSQIP) and administrative datasets (e.g., Medicare, Marketscan). 

• Oversees and guides resident and fellow-led research projects by providing data support and analytic mentorship.

• Collaborates with study investigators to design analytic plans and interpret results.

• Maintains organized, reproducible code and data management workflows.

• Serves as the dedicated research data resource for multiple projects across varying stages of development.

• Develops and maintains research databases, ensuring data integrity and compliance.

• Assists in preparing datasets, figures, tables, and summaries for grant proposals, manuscripts, and presentations.

• Coordinates with external collaborators and data partners as needed.

• Supports data processing and reporting of a multistate surgical quality improvement collaborative.

• Analyzes moderately complex data sets for the purpose of extracting and purposefully using applicable information.

• Provides professional support to staff or faculty members in defining the project and applying principals of data science in manipulation, statistical applications, programming, analysis and modeling.

• Builds and analyzes statistical models and reproducible data processing pipelines using knowledge of best practices in machine learning and statistical inference. Serves as a single point of contact for all requests and engages other IT resources to assist as needed. May partner with other campus teams to assist faculty with data science related needs.

• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

Certifications:

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Preferred Qualifications

Education:

• Master's degree in Biostatistics, Epidemiology, Data Science, Public Health, Health Informatics, or related field.

Experience:

• Experience mentoring or supporting trainee research (e.g., residents, fellows).

• Prior experience working in an academic medical center or research institute setting.

Preferred Competencies

• Proficiency in statistical software (e.g., R, SAS, or Stata) and data management tools.

• Familiarity with working with large clinical datasets or national registries (e.g., NSQIP).

• Strong understanding of clinical research principles and methodology.

• Excellent organizational skills and ability to manage multiple projects simultaneously.

• Familiarity with health services research or outcomes-focused studies.

• Knowledge of database query languages (e.g., SQL).

Application Documents

• Resume (required)

• Cover Letter (preferred)

Job Family

Research

Role Impact

Individual Contributor

Scheduled Weekly Hours

40

Drug Test Required

No

Health Screen Required

No

Motor Vehicle Record Inquiry Required

No

Pay Rate Type

Salary

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FLSA Status

Exempt

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Pay Range

$70,000.00 - $100,000.00

The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.

Benefits Eligible

Yes

The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.

Posting Statement

The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

 

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

 

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

 

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