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# Data Analyst, Level I (Remote)

- **Company:** University of Arizona
- **Location:** United States (Remote available)
- **Experience:** Starter
- **Salary:** $53,039.0 - $66,299.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Excel, Data Analysis, Microsoft Outlook, Data Mining, Data Visualization, Microsoft Office, Microsoft PowerPoint, SQL Databases, Data Management
- **Published:** August 3, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=39cc25a685c1fbe2

## About the Role

* Ability to communicate effectively with different groups/individuals.
 * Ability to handle confidential and sensitive information.

The job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

Minimum Qualifications:

 * Bachelor's degree or equivalent advanced learning attained through experience required.
 * 1 year of relevant work experience may be required.

Preferred Qualifications:

 * Experience with Microsoft Suite (Excel, Outlook, SQL, PowerPoint, etc).
 * Experience with CampusVue/Anthology.

## Description

The Data Analyst, Level I position is a full-time employment opportunity. Reporting to the Director of Institutional Research, the Data Analyst, Level I provides data support to requests from leadership, faculty, staff, and external entities by validating and analyzing data, data mining, data submission to external sources, as well as by preparing reports to support decision-making., * Perform data management activities such as validating and cleaning data, ensuring data meets the set requirements to a high-level of accuracy and integrity.

 * Analyze quantitative and qualitative data and provide analytical support to the Office of Institutional Effectiveness, Academics, Student Affairs, and the institution at large.
 * Ensure reports are of required quality and adhere to recognized best practices in academics, data visualization, and data science.
 * Prepare data visualizations and reports for presentation of analyses and results.


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