STAR Data Analyst

STAR Data Analyst - Job Description

Student Technology, Advising, and Retention (STAR) Data Analyst

SUMMARY:

The STAR Data Analyst serves as the analytical backbone of the Student Technology, Advising, and Retention (STAR) project. This position is responsible for developing predictive analytics, monitoring student success outcomes, maintaining data governance protocols, and creating the dashboards and reporting systems that support project implementation, continuous improvement, and U.S. Department of Education reporting requirements. The Data Analyst will integrate data across academic, advising, tutoring, career services, and AI platforms to support early identification of at-risk students and evaluate the effectiveness of project interventions.

RESPONSIBILITIES:

• Develop, maintain, and continuously refine dashboards and reporting tools that monitor STAR performance measures, including retention, persistence, credential attainment, workforce readiness outcomes, student engagement, and utilization of support services.
• Design and implement predictive analytics models that identify students who may benefit from academic, financial, advising, or student support interventions.
• Integrate, validate, and analyze data from Ellucian Student Signature, Blackboard, Tutor.com, Salesforce, career services platforms, and other project systems.
• Lead data quality, cleansing, validation, and governance activities to ensure accuracy, consistency, and reliability of project data.
• Produce quarterly and annual performance reports for project leadership, the U.S. Department of Education and stakeholders.
• Collaborate with advisors, faculty, student support personnel, and project staff to translate data into actionable student success strategies.
• Establish and maintain FERPA-compliant data governance procedures, data access protocols, and reporting standards.
• Provide data analyses and performance updates to the Project Director, Advisory Board, university leadership, and partners.
• Coordinate data collection, validation, and reporting activities with the external evaluator to support evaluation activities.
• Support continuous improvement efforts by identifying trends, monitoring implementation progress, and recommending data-informed adjustments to project activities.
• Assist with dissemination of project outcomes through presentations, reports, publications, and institutional communications.
• Understand and abide by all external and internal regulations and policies. This includes NCAA, GLIAC, and national affiliations associated with athletics or other role-specific regulations.
• Provides GREAT customer service, anticipating and exceeding the needs of our customers.
• Demonstrate and promote the University's Cultural Values.
• Perform other duties as assigned.

QUALIFICATIONS:

• Bachelor’s degree, Master’s preferred, in Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Institutional Research, or a related field required.
• Experience working with large datasets, reporting systems, dashboards, and data visualization tools.
• Demonstrated experience with predictive analytics, statistical analysis, and performance measurement.
• Experience working with SQL, relational databases, and data integration processes.
• Knowledge of higher education data systems, student success metrics, retention analytics, or institutional research practices preferred.
• Experience supporting program evaluation, grant reporting, or performance measurement initiatives preferred.
• Strong analytical, problem-solving, organizational, and communication skills.
• Knowledge of FERPA, data privacy, and data governance best practices.
• Experience using AI for data analysis.
• Business office environment. Prolonged sitting and standing. Use of personal computer and telephone (eye and hand strain). Ability to lift classroom materials, etc., up to 50 lbs.
• Occasional travel, including overnight stays.
• Must be able to work an irregular schedule, evenings or Saturday as needed, additional hours during peak times or as required.