Senior Research Associate

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Job Title:

Senior Research Associate Department:

Academic Affairs Administration | Institutional Research and Planning Institutional Research and Planning Office Overview The Office of Institutional Research and Planning (IRP) provides accurate, timely, consistent, and actionable data and integrates analytics across multiple domains (student, faculty, human resources, fiscal, research, facilities, and more) to support evidence-based decision-making at The Ohio State University.

IRP provides leadership, vision, and strategic direction in building a data-informed decision culture by collaborating with campus stakeholders in broadening data sharing, data governance, actionable insight development, operational effectiveness, and professional skill development. We engage in institutional research, official reporting, institutional effectiveness, data visualization, survey research, assessment and accreditation data support, and applied analytics to enhance student success as well as overall university and operational effectiveness.

Position Summary The Senior Research Associate (Research S4) serves as a senior methodologist in IRP, reporting directly to the Associate Vice President. Centered on advanced analytics , predictive analytics , and survey research , this role designs and executes complex statistical models, and large-scale survey instruments to evaluate program effectiveness, assess student success and academic excellence interventions, and advance strategic priorities under the Academic Excellence Plan and University Strategic Plan.

This position collaborates across campus offices and areas such as the Center for Career Excellence, Office of International Affairs (OIA), Strategic Enrollment Management (SEM) Undergraduate Education, Graduate Education, Student Life, Office of Technology and Digital Innovation (OTDI), and academic departments.

Key Responsibilities & Percentage Breakdown
35% — Advanced Data Analytics Advanced Analytics:
Executes advanced quantitative methods (linear/logistic regression, mixed methods (e.g., text analytics), multivariate analysis, survival analysis, propensity score matching using R, SPSS, SAS, and Stata.

Predictive Analytics, Modeling & Projections:
Leads the development, validation, and maintenance of predictive analytics, statistical models, and time-series forecasting algorithms, or machine learning for student success (e.g., retention, persistence, and graduation rates) and other strategic priorities.

Ranking Simulations:
Simulates  what-if  scenarios for national and global university rankings (USNWR, QS, THE), focusing on international student success metrics, global mobility, and peer benchmarking.
25% — Full-Lifecycle Survey Research & Program Evaluation, Assessment Survey Research & Instrument Design:
Designs…