Department
BSD PHS - Martinez Cardoso Lab
About the Department
Public Health Sciences (PHS) is the home in the Biological Sciences Division to biostatistics, epidemiology and health services research. These core fields in public health research share a focus on the development and implementation of complex analytic methods to understand the determinants of health, the efficacy of experimental treatments, and the structure of health care at the population level. Bringing together these fields in one department underscores their commonality and enhances opportunities for interdisciplinary research. Faculty members lead local, national, and international studies, and also welcome opportunities to collaborate with faculty across the Biological Sciences Division and the university. Substantively, our research themes include social and environmental determinants of health, genetics and disease, the economics of health care, and the evaluation and implementation of new technologies in public health and clinical care. In terms of methodological expertise, areas in which our faculty has developed innovative approaches include: risk factor measurement; multilevel, clustered and longitudinal data; clinical trials; administrative health data; social networks; and statistical methods to assess the genetic and molecular basis of disease.
Job Summary
The Embodying Racism Lab, in the Department of Public Health Sciences, seeks a research data scientist to support research projects examining how government policies influence social determinants of health and contribute to health disparities in the U.S. Our work employs quantitative methods with large-scale health, policy, and administrative data.
Responsible for all aspects of research projects and research facilities. Plans and conducts clinical and non-clinical research; facilitates and monitors daily activities of clinical trials or research projects. Directs engineering and technical support activities to develop and maintain tools and computational methods needed to gather and analyze data.
This position is expected to begin on 8/1/25 and end on 7/31/26, contingent upon operational needs and funding availability. If your position ends sooner than the expected end date, you will be given a minimum of one pay period’s written notice (If exempt: one month, If non-exempt: 2 weeks), or pay in-lieu of notice.
This at-will position is wholly or partially funded by contractual grant funding which is renewed under provisions set by the grantor of the contract. This position is expected to begin on August 1, 2025 and end on July 31, 2026, contingent upon operational needs and funding availability. Employment will be contingent upon the continued receipt of these grant funds and satisfactory job performance. If your position ends sooner than the expected end date, you will be given a minimum of one pay period’s written notice (If exempt: one month, If non-exempt: 2 weeks), or pay in-lieu of notice.
Responsibilities
Lead data preparation and analysis for 2-3 lab projects such as: Compiling administrative data across U.S. counties to study structural drivers of health; cleaning national birth outcomes data to uncover patterns across counties; linking Census data with hospital records to assess underserved communities on Chicago's South Side; creating visualizations of immigration policy data across U.S. counties.
Assist with project administration including grant reporting, hiring and supervising student staff, data management and lab operations.
Support manuscript preparation including drafting text, creating figures and tables, submitting to portals, and addressing revisions.
Assists in analyzing data for the purpose of extracting applicable information. Performs research projects that provide analysis for a number of programs and initiatives.
May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad-hoc basis.
Collects, organizes, and may analyze information from the University's various internal data systems as well as from external sources.
Maintains and analyzes statistical models using general knowledge of best practices in machine learning and statistical inference. Performs maintenance on large and complex research and administrative datasets. Responds to requests and engages other IT resources as needed.
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 years of work experience in a related job discipline.
Certifications:
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Preferred Qualifications
Education:
Experience:
Technical Skills or Knowledge:
Proficiency in data manipulation using R, STATA, or Python.
Knowledge of statistical methods, research design, causal inference, and econometrics, and their application.
Preferred Competencies
Self-starter with the ability to work independently, troubleshoot challenges, and take initiative.
Passion for public health, public policy, and addressing health disparities.
Working Conditions
Application Documents
Resume/CV (required)
Cover Letter (preferred)
When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
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
Hourly
FLSA Status
Non-Exempt
Pay Range
$24.04 - $31.25
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 theBenefits 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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