This job was posted by : For more information, please see: Department UL Inclusive Economy Lab About the Department About the Department Founded in 2015, The University of Chicago Inclusive Economy Lab conducts rigorous research that expands economic opportunity for people harmed by discrimination, disinvestment, and segregation. One of five Urban Labs based at the Harris School of Public Policy, the Inclusive Economy Lab is led by Pritzker Director Marianne Bertrand, Chris P. Dialynas Distinguished Service Professor of Economics at the Booth School of Business. Job Information Job Summary: Temporary Data Analyst Interns will assist project staff with quantitative data analysis tasks for their various research projects. We are looking for motivated individuals who are passionate about evidence-based policy and promoting economic stability and opportunity. This internship is a great opportunity to help you improve your research and data analysis skills, while contributing to rigorous research at IEL. Responsibilities: Data entry, cleaning, and merging. Collaborating with project teams to implement analysis plans. Analyzing data for descriptive, experimental, and quasi-experimental studies. Creating data visualizations and summary statistics. Writing, formatting, and editing technical sections of reports and works for dissemination. Completing administrative tasks for IEL projects or operations. Performing other related work as needed. Competencies: Ability to engage thoughtfully with issues related to race, identity, and equity. Ability to work both independently and collaboratively with others. Ability to work discreetly with sensitive and confidential data. Knowledge of research theory, methods, and literature. Strong interpersonal, oral, and written communication skills. Strong organizational skills and attention to detail. Additional Requirements Education, Experience, or Certifications: Education: High School Diploma required. Significant progress towards or completion of a degree in economics, public policy, statistics, or a related social science discipline preferred. Technical Knowledge or Skills: Experience with R or Stata. Experience with data cleaning and manipulation. Experience with Microsoft Office Suite. Pay Range: \$17.00 -\$25.00 Required Documents: Resume Cover letter, including a list of the IEL program areas ranked by your level of interest (College and Career Success, Financial Security, Housing Stability, and Quality Jobs). When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application. Benefit Eligibility No Requires Compliance with University Covid-19 Vaccination Requirement No Pay Frequency Hourly Pay Range Depends on Qualifications Scheduled Weekly Hours 37.5 Union Non-Union Job is Exempt No Drug Test Required No Motor Vehicle Record Inquiry Required No Health Screen Required No Posting Date 2024-01-23 Remove from Posting On or Before 2024-07-23 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 a plication 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 circumstance
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