Department
Harris School Pre-Docs, Temps and Non-Student Research Assistants
About the Department
Job Summary
The successful candidate will have experience in applying a variety of statistical modeling and data analysis techniques to datasets in real-world settings. From project inception to delivery, the research assistant will contribute to all facets of data collection and cleaning, model development, and implementation.
Responsibilities
Works with partners and members of the research team to propose and implement analytical approaches to solving specific research questions.
Cleans, transforms, merges, and matches between large and complex research and administrative datasets.
Builds statistical models for a variety of research projects.
Performs sampling, power analysis, and randomization.
Prepares results for memos, presentations, and academic papers targeting both policymakers and researchers.
Assists with drafting papers.
Writes statistical computer programs and reviews computer output for consistency and quality.
Maintains technical and administrative support for a research project.
Analyzes and maintains data and/or specimens. Conducts literature reviews. Assists with preparation of reports, manuscripts and other documents.
Performs other related work as needed.
Minimum Qualifications
Education:
Minimum requirements include a college or university degree in related field.
Work Experience:
Certifications:
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Preferred Qualifications
Education:
Master’s degree in economics, sociology, public policy, statistics, computer science, or a closely related field.
Experience:
Experience working with statistical programming languages.
Strong interest in social policy, especially crime and education policy.
Technical Skills or Knowledge:
Experience in data analysis.
Strong quantitative skills.
Ability to manage multiple projects simultaneously and meet tight deadlines.
Preferred Competencies
R or Python experience strongly preferred.
Excellent organizational skills and attention to detail.
Ability to work both independently and as a team member.
Ability to work carefully with sensitive and confidential data.
Candidates are encouraged to highlight experience in the following areas: Working with large, complex, and/or administrative datasets.
Program evaluation methods (e.g., difference-in-differences, propensity score matching, regression discontinuity).
Creating data visualizations.
Conducting predictive analyses using random forest or related algorithms.
Imputing missing data.
Working Conditions
Predoctoral Fellow will be based out of Chicago, IL.
Application Documents
Resume (required)
Cover Letter (required)
Reference Contact Information (2) (required)
Unofficial Transcript (required)
When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.
Job Family
Role Impact
Scheduled Weekly Hours
Drug Test Required
Health Screen Required
Motor Vehicle Record Inquiry Required
Pay Rate Type
FLSA Status
Pay Range
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
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 Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, 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.
Staff 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.
We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.
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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