Senior Research Associate

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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.

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.

• 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.

• Survey Research & Instrument Design: Designs survey instruments, manages Qualtrics administration, ensures data validity/reliability, and analyzes survey outputs to identify student experience trends.

• Program Evaluation and Outcomes Assessment: Conducts quantitative and qualitative impact studies to assess interventions, academic programs, learning outcomes, and student support interventions. Understanding of research design and applied research methods.

• Data Integration: Merges survey data with longitudinal institutional datasets for comprehensive student lifecycle evaluations.

• Career, Work-Based Learning, Career & Experiential Learning Evaluation: Evaluates post-graduation career outcomes, salary trajectories, and the impact of work-based learning (internships, co-ops, undergraduate research, clinicals).

• Data Integration: Merges and cleans complex datasets, including Post-Secondary Employment Outcomes (PSEO), Graduation First Destination Survey, Handshake, 12Twenty, and labor market statistics.

• Career Analytics Liaison: Serves as the primary analytics partner to the Center for Career Excellence to assess program ROI and workforce alignment.

• Executive Visualization & Dashboards: Constructs interactive, executive-ready dashboards and tracking tools in Tableau, Power BI, Python, or R.

• Report Writing & Communication: Synthesizes complex quantitative analyses, survey outputs, and predictive models into formal narrative reports, executive briefings, and visual presentations.

• Data Storytelling: Translates technical statistical concepts into plain-language data stories that clarify complex higher education metrics and drive data-informed decision-making across non-technical audiences. Enhances data fluency and translating data into insights across the university.   

• Campus Partnerships: Collaborates directly with academic departments, the Center for Career Excellence, Office of International Affairs (OIA), Strategic Enrollment Management (SEM), Student Life, Undergraduate Education, and Graduate Education.

• Executive Policy Support: Translates complex analytical findings into policy briefs and strategic recommendations for Deans, Vice Provosts, and Senior Leadership.

• IR & IT Alignment: Partners with Institutional Research and IT colleagues to ensure data accessibility, system integrity, and operational alignment.

• Demonstrated experience in advanced analytics, predictive analytics, statistical modeling, or machine learning, Predictive Modeling: Expertise in advanced data analytics, multivariate statistics, statistical prediction modeling, forecasting, and ranking methodology simulations.

• Survey Research & Program Evaluation: Applied mastery of survey instrument design, Qualtrics administration or other survey research tools, sampling, data validity, and impact evaluation methods.
• Advanced statistical analysis and software proficiency: Hands-on proficiency in R, SPSS, SAS, or Stata.
• Data Visualization, Presentation, & Communication Skills: Advanced proficiency in executive report writing, oral presentations, interactive Tableau/Power BI dashboard development, and compelling data storytelling for non-technical stakeholders.
• Domain Expertise: Practical experience integrating public, internal and external data sources for understanding career outcomes and student success (PSEO, Graduation/First Destination, Handshake, 12Twenty, National Student Clearing House, OIA international student data).
• Ethical AI Utilization: Responsibly applies AI tools to streamline coding and exploratory analysis while ensuring auditability, fairness, and data privacy 

• Education: Master’s degree or Ph.D. in Statistics, Data Analytics, Quantitative Research Methodology, Economics, Higher Education Evaluation, Social Sciences, or a related quantitative field.
• Experience:
  • Master’s Degree: Minimum of 5 years of relevant professional experience.
  • Ph.D.: Minimum of 3 years of relevant experience (Post-doctoral work and Graduate Research Assistant [GRA] experience will count toward this requirement)
  • Experience must be in higher education assessment, institutional research, data analytics, or survey research.
    

• Technical & Analytical Skills:
  • Demonstrated experience in quantitative advanced analytics, predictive analytics, statistical modeling, or machine learning,
  • Proficiency in statistical software tools, including R, SPSS, SAS, or Stata.
  • Demonstrated experience in survey research methods, instrument design, and administration (e.g., Qualtrics).
  • Experience conducting higher education program evaluations, outcome assessments, and intervention impact studies.
  • Excellent communication, report writing, presentation, and data visualization skills, including dashboard development in Tableau, Power BI, or Python.
    

• • Education: Ph.D. or terminal degree in a quantitative field. 
  • Experience: Quantitative research experience within an R1 university institutional research or assessment office.
  • Advanced Capabilities: Proven track record in enterprise predictive analytics, ranking models, executive report writing, and high-level data storytelling.
  • Experience working with career outcome data or multi-source platform integration (e.g., PSEO, First Destination Survey, Handshake, 12Twenty).
  • Experience with ranking projection models. What-if tools and ranking predictions (e.g., USNWR, QS Shanghai) 
  • Proficiency in statistical software and query tools, including R, Python, SQL, SPSS, SAS, or Stata.

Please submit both a cover letter and a resume to be considered for this opportunity.

The target hiring range for this job profile is $ 104,000 - $110,000  The actual salary paid to an individual will vary based on multiple factors, including but not limited to, education, years of experience, internal equity, etc. 

Function -  Research and Scholarship

Sub Function -  Research

Band -  Individual Contributor - Specialized

Level -  S4

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The university is an equal opportunity employer, including veterans and disability.