Institutional Research Data Analyst, Office of Planning, Evaluation, and Institutional Research - UT Chattanooga

University of Tennessee•Chattanooga, TN

1d•$55,000 - $63,000•Onsite

About The Position

The primary objective of the Institutional Research Data Analyst position is to provide actionable insights and recommendations to support academic program planning, student success, strategic planning, resource allocation, and continuous improvement across the institution. The position requires a high level of accuracy, extraordinary attention to detail, solid proofreading skills, the ability to multi-task and meet deadlines, and the ability to adhere to ethical and legal standards in institutional research.

Requirements

Bachelor’s degree in Psychology, Data Science, Computer Science, Information Systems, Business Administration, or a relevant field.
At least 2 years of experience in data analysis, reporting, or data management, preferably working with complex data systems or large datasets.
Experience working directly in Institutional Research, Institutional Effectiveness, Assessment, or Data Analytics/Business Intelligence offices.
Knowledge of descriptive and inferential statistics and software (e.g., SPSS, R, SAS).
Enthusiasm for problem-solving; demonstrated ability to create effective solutions to complex tasks.
Working understanding of key institutional business practices and reporting metrics.
Strong written and verbal communication skills, with the ability to present data findings clearly and translate technical information for non-technical audiences.
Ability to manage multiple projects and deadlines simultaneously while working collaboratively in a team environment.
Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa.
A cover letter and resume are required for consideration. The cover letter should be included in the same document as your resume and should specifically express your interest in the position, highlighting relevant skills and experience.

Nice To Haves

Master's degree in Analytics, Education, Psychology, Business, or a related field
Prior experience in a higher education Institutional Research office or a similar environment is highly desirable.
Familiarity with standard higher-education reporting and survey requirements, such as IPEDS reporting, accreditation data submissions, or National Student Clearinghouse reports. This includes understanding the definitions of common institutional metrics and ensuring consistent reporting of these figures.
Experience with administrative student information systems used in higher education (e.g., Banner, PeopleSoft) is beneficial.
Knowledge of data governance principles and data management best practices within large organizations is also advantageous.

Responsibilities

Design, implement, and contribute to projects using appropriate research methodologies and analytical techniques to identify trends, patterns, and correlations in key performance metrics (e.g., enrollment, retention, outcomes) and operational efficiencies (e.g., course section offerings, faculty workload).
Interpret these findings and translate them into clear, actionable insights and recommendations for institutional leadership and other stakeholders.
Design, develop, train, and test predictive models to identify and prioritize student success outcomes for the College using a variety of data mining and advanced statistical analysis techniques.
Conduct predictive modeling and forecasting to anticipate future enrollment trends and resource needs.
Prepare required institutional reports (e.g., IPEDS UT System, THEC, and other federal/state reports) accurately and on time.
Ensure all compliance data submissions meet defined standards and deadlines.
Respond to ad-hoc requests for data or analysis from campus stakeholders, providing accurate and official information promptly.
Document the process for completing reports.
Interpret data findings and deliver clear, actionable insights to key stakeholders, including academic administrators, faculty members, and institutional leadership.
Lead training sessions to enhance data literacy and encourage data-informed decision-making across the institution.
Stay informed on best practices in data analytics and higher education.
Proactively seek to respond to institutional needs.