Data Science Analyst -TCOM

Biological Sciences Division at the University of Chicago

Chicago (IL)

On-site

USD 33,117 - 43,050

Full time

14 days+

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Benefits offered by this job

Health insurance
Retirement benefits
Paid time off

Job summary

An academic research division is seeking a Data Science Analyst to provide technical support for online training systems. The role involves analyzing data, monitoring user support channels, and collaborating with technical teams to resolve issues. Applicants should possess a degree in a related field and knowledge of Learning Management Systems. This is a full-time position based in Chicago, offering a pay rate between $24.04 and $31.25 per hour, with benefits included.

Qualifications

  • Minimum < 2 years of work experience in a related job discipline.
  • Knowledge of Learning Management Systems and Zendesk.

Responsibilities

  • Provide technical assistance to help learners navigate online training systems.
  • Monitor and respond to LMS support messages.
  • Collaborate with technical support teams to resolve issues.

Skills

Learning Management Systems
Strong communication skills
Detail-oriented
Proficiency with Microsoft Office 365

Education

College or university degree in related field

Tools

Zendesk

Job description

About The Department

To transform mental health through compassionate, innovative interdisciplinary care, pioneering research, and the education of future leaders dedicated to advancing the well‑being of individuals, families, and their communities.

Department

BSD PSY - Lyons Lab

Job Summary

The Data Science Analyst provides technical assistance to help learners access and navigate online training systems. The Specialist serves as the liaison between end-users and the learning platform. Under direct supervision, this job performs a broad range of operational activities, which may include collecting, organizing, and analyzing information from the University's various internal data systems as well as from external sources. This job also performs assignments related to data manipulation, statistical applications, programming, analysis and modeling.

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 elevate 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

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.

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)
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

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 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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