Department
BSD PSY - Lyons Lab
About the Department
Job Summary
Responsibilities
Collect, clean, and organize data from multiple sources.
Conduct analyses using statistical and computational methods.
Develop data visualizations, dashboards, and reports to share findings.
Collaborate with program, training, and operations teams to apply data insights to projects.
Ensure data quality, security, and integrity across systems.
Contribute to cross-team initiatives by embedding data-informed practices.
Develop and code data dictionaries for discrete data.
Write, Implement, and develop efficient code and machine learning tools and pipelines for data processing and analysis.
Work with collaborators to implement emerging external computational tools for program data.
Develop training material.
Keep lab's knowledge-based trainings up to date.
Calibrates data between large and complex research and administrative datasets. Guides and may set the operational protocols for collecting and analyzing information from the University's various internal data systems as well as from external sources.
Designs and evaluates statistical models and reproducible data processing pipelines using expertise of best practices in machine learning and statistical inference.
Provides expertise for high level or complex data-related requests and engages other IT resources as needed.
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.
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:
Advanced degree.
Experience:
Experience in python including torch and scikit-learn libraries strongly preferred.
Experience in working with image data or unstructured text data with large language models.
Preferred Competencies
Proficiency in Python, R, SQL, or other statistical programming languages.
Experience with data visualization platforms such as Tableau or Power BI.
Strong analytical and problem-solving skills.
Ability to communicate complex findings in accessible ways.
Detail-oriented with a commitment to data accuracy and quality.
Experience working with research or program evaluation data strongly preferred.
Proficiency in Microsoft Office 365.
Strong Analytical skills.
Problem-solving skills.
Organizational skills.
Verbal and written communication skills.
Ability to work independently and as part of a team.
Application Documents
Resume (required)
Cover Letter (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 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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