"Research and Programmer Analyst"

Position Overview

The Research and Programmer Analyst (RPA) is a key analyst role within the Institutional Research and Strategic Effectiveness (IRSE) office, responsible for helping to integrate accurate, valid, and reliable data across a range of complex operating systems, applications, networks, and databases. Through a research lens, the RPA will develop, modify, and optimize programming code to construct and manage data files in preparation for institutional analysis, ensuring data is structured in a way that supports reporting and decision-making. The RPA will provide comprehensive data management, programming, and analytical support to help advance institutional goals, state priorities, and accreditation standards. This role involves managing large datasets, performing complex data compilation, and supporting predictive modeling and analytics to measure the effectiveness of institutional programs.

A critical aspect of this role is ensuring the ease of data access for both internal and external stakeholders. The RPA will support data governance and literacy across the campus, empowering users to leverage data in a way that enhances institutional effectiveness. Furthermore, the RPA will apply a social justice framework when developing algorithms, creating data structures, and conducting analyses to ensure that all data practices are inclusive, equitable, and reflective of the diverse student population. By ensuring that institutional data is reliable, accessible, and analyzed through an equitable lens, the RPA will be instrumental in supporting evidence-based decision-making that drives student success and institutional improvement.

Essential Job Duties

Data Collection, Programming, and Analytics

• Have a complete understanding of institutional data, databases, and source data to analyze and develop systems and technology-based solutions that enhance the unit's ability to perform data analytics, evaluation, and research studies, and report findings accurately, validly, and reliably.
• Utilize tools such as SQL, SPSS, R, and Python for advanced data analysis and to generate actionable insights from student success programs. Apply statistical analysis methods to perform predictive modeling and assess key trends related to student retention, engagement, and graduation rates.
• Perform longitudinal data analysis to track trends and assess the effectiveness of student success programs.
• Support complex data compilation, predictive modeling, statistics, and trend analysis activities to measure key initiatives.
• Collect and analyze both quantitative and qualitative data related to student success outcomes.
• Synthesize findings from both qualitative and quantitative data to recommend program improvements and best practices.

Research/Evaluation Activities

• Support and engage in a wide range of complex evaluation and applied research studies on various key initiatives related to student success to measure effectiveness and/or impact.
• Design and execute program evaluations to measure the impact of student success initiatives.
• Contribute to research projects involving programming reports to gather data for analyses of student success and program outcomes using institutional data by applying a variety of techniques as well as advancing the application of predictive modeling approaches.
• Collaborate with program leads to establish evaluation frameworks, including objectives, metrics, and data collection strategies.
• Ability to perform research activities that may require analysis of multiple factors or data sources.
• Stay abreast of emerging trends and best practices in student success research and institutional assessment.

Social Science and Survey Design Integration

• Adhere to appropriate theoretical framework, research designs, and methodological approaches to facilitate producing competent research and evaluation studies to produce valid and reliable outcomes.
• To complement quantitative data and provide a holistic view of student experiences, the ability to conduct qualitative research, including interviews and focus groups.
• Design and deploy surveys to gather student feedback and evaluate programmatic impact.
• Perform appropriate analyses of survey data to draw meaningful conclusions.
• Ensure surveys are inclusive, accessible, and valid across diverse student populations.

Reporting & Visualization

• Prepare clear, comprehensive reports for stakeholders.
• Develop systematic reporting capabilities, documentation, and web-based sites related to assigned projects to support operational continuity and institutional effectiveness.
• Apply data visualization techniques (e.g., Tableau, Power BI) to develop tables, dashboards, and other approaches to clearly communicate insights into student success and institutional performance.

Collaboration & Consultation

• Collaborate with IRSE team and institutional stakeholders to address student success challenges.
• Advise stakeholders on data-driven strategies to improve student outcomes.
• Perform quality checks on own work and the work of other contributors to ensure outcomes are valid, reliable, and accurate.

Knowledge, Skills, and Abilities

• Data Analysis & Statistical Techniques: Proficient in quantitative and qualitative analysis, including longitudinal trends, regression analysis, and predictive modeling. Proficiency in using appropriate software to perform data analysis (e.g., SPSS, SAS or R).
• Systems & Visualization: Familiarity with coding/programming, database management, and interfacing with various data ecosystems (e.g., SQL, Python, experience in Student Information System (SIS) such as Banner, Colleague or Jenzabar). Demonstrated ability to design and develop interactive dashboards and reports in Tableau or similar.
• Survey Design & Evaluation: Expertise in designing, deploying, and analyzing surveys, ensuring accessibility and validity for diverse student populations.
• Research Methodologies: Knowledge of applied research, program evaluation, and social science frameworks (e.g., student development theory, learning theory).
• Communication & Reporting: Ability to present complex data clearly in reports and visualizations for diverse audiences.
• Collaboration & Consultation: Strong interpersonal skills for working with faculty and stakeholders to improve student success initiatives.
• Project Management: Ability to manage multiple research projects, ensuring timely completion and alignment with institutional goals.
• Critical Thinking & Problem Solving: Capacity to analyze complex issues, synthesize findings, and recommend data-driven solutions for improving student success programs.

Required Qualifications

• Bachelor's degree in social sciences, data/computer science, mathematics, education, economics, or a related field.
• At least three progressive years of experience in data analytics, research, or program evaluation, with proficiency in programming languages such as SQL, SPSS, R, and/or Python.
• Strong understanding of data architecture, information ecosystems, and database management techniques including report writers such as Argos or Insights.
• Experience with data visualization modeling such as Tableau or Power BI.
• Proficiency in quantitative and qualitative analysis, including experience in longitudinal studies, regression analysis, and predictive modeling.
• Demonstrated experience in survey design and evaluation, with a focus on ensuring data accessibility and validity across diverse populations.

Preferred Qualifications

• Advanced graduate degree in social sciences, data/computer science, mathematics, education, economics, or a related field.
• Four or more years of experience in data analytics, research, or program evaluation, with proficiency in programming languages such as SQL, SPSS, R, and/or Python.
• Advanced skills with data visualization in Tableau or Power BI.
• Experience in Institutional Research, assessment, and/or program evaluation within higher education.
• Advanced skills in statistical modeling for large data sets, including techniques such as regression analysis, structural equation modeling (SEM), and predictive modeling.
• Advanced skills in SQL, Python, and other programming languages for building, maintaining, and optimizing databases and data management applications.
• Advanced report writing skills in Argos or Insights.
• Experience with data ecosystem development, including data conversion and integration of Student Information Systems (e.g., Ellucian, Colleague).