Student Success Analyst, Institutional Research & Academic Analytics

About the role

The Office of Institutional Research & Academic Analytics at the University of Cincinnati is seeking a Student Success Analyst to join the Academic Analytics team. Reporting to the Director of Student Success and Research Analytics, this role will leverage statistical and predictive models to support institutional priorities including student retention, enrollment, and scholarship strategy.

Responsibilities

• Develop and apply statistical and predictive models (e.g., regression, classification, forecasting) to support institutional priorities including student retention, enrollment, and scholarship strategy.
• Conduct exploratory data analysis (EDA) to identify patterns, trends, and anomalies in large institutional datasets, with an emphasis on student success outcomes.
• Partner with academic and administrative units to deliver practitioner-facing analytics, presenting findings in formats that are accessible, actionable, and appropriate for non-technical audiences including advisors, program staff, and college leadership.
• Incorporate qualitative methods (e.g., survey analysis, interview synthesis, thematic coding) alongside quantitative approaches to provide richer context for student success and recruitment questions.
• Design, build, and maintain dashboards and data visualizations for internal stakeholders and leadership; publish outputs appropriate for web-based dissemination.
• Collaborate with Digital Technology Solutions (DTS) and data governance teams to access, transform, and validate data needed for analysis.
• Connect data across multiple sources and phases of the student lifecycle — admissions, advising, academic performance, and post-graduation outcomes — to support integrated, evidence-based planning.
• Employ third-party data resources (e.g., National Student Clearinghouse, ACT, College Board) to contextualize institutional trends and support benchmarking.
• Maintain documentation for models, analytical workflows, and data definitions to support transparency and reproducibility.
• Perform related duties based on departmental need.

Requirements

• Bachelor's Degree in a quantitative or data-intensive field such as Statistics, Mathematics, Data Science, Computer Science, Information Systems, or a related social science discipline with a strong analytical component.
• Three (3) years of relevant experience in data analysis or applied analytics, including demonstrated proficiency in R or another analytical programming language (Python, SAS, or SQL).
• Master's degree in a relevant field preferred.
• Higher education or institutional research experience preferred.
• Experience with student success, retention, or enrollment analytics preferred.
• Experience with data visualization tools such as Tableau, Power BI, or similar platforms preferred.
• Familiarity with qualitative research methods or mixed-methods analytical approaches preferred.
• Familiarity with machine learning concepts or tools and interest in expanding into applied ML work preferred.
• Exposure to cloud data environments or warehouse platforms (e.g., Snowflake, BigQuery) preferred.

Qualifications

• Considered Master's degree in a relevant field.
• Higher education or institutional research experience.
• Experience with student success, retention, or enrollment analytics.
• Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
• Familiarity with qualitative research methods or mixed-methods analytical approaches.
• Familiarity with machine learning concepts or tools and interest in expanding into applied ML work.
• Exposure to cloud data environments or warehouse platforms (e.g., Snowflake, BigQuery).

Skills

• Statistical and predictive modeling skills.
• Data visualization and dashboard building skills.
• Qualitative research methods.
• Machine learning concepts.

Benefits

• Comprehensive Tuition Remission
• Robust Retirement Plans
• Competitive Salary Based on Experience
• Flexible Spending Accounts & Wellness Programs
• Professional Development & Mentorship Opportunities

Pay

[[custRCM_PostingSalary]]

Schedule

Hybrid work arrangement.