About this Data Science Analyst -TCOM role at University of Chicago
Department
BSD PSY - Lyons Lab
About the Department
Job Summary
Responsibilities
Monitor and respond promptly to messages in the LMS support email inbox and voicemail line.
Provide clear, compassionate, and timely support to learners through phone and email.
Troubleshoot issues with the LMS and know when to escalate or redirect to other team members or the platform provider’s support desk.
Collaborate with the LMS provider’s support team to identify, report, and help resolve technical issues.
Track and share patterns or recurring concerns that may indicate broader system issues.
Work closely with the Technology & User Support Lead, teaching and learning specialists, and program administrators to improve learner support.
Contribute to cross-team projects as needed, such as data entry, communications, or general tech assistance.
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:
Certifications:
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Preferred Qualifications
Experience:
Learning Management Systems.
Technical Skills or Knowledge:
Knowledge Learning Management Systems and Zendesk.
Preferred Competencies
Strong communication skills with the ability to explain technical information in clear and supportive ways.
Patience, empathy, and commitment to learner success.
Detail-oriented and organized, with the ability to manage multiple requests efficiently.
Comfort with technology and ability to learn new learning management systems.
Excellent communication and coaching abilities.
Proficiency with Microsoft Office 365 and LMS platforms.
Organizational skills.
Verbal and written communication skills.
Work independently and as part of a multidisciplinary team.
Application Documents
Resume/CV (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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