Senior Research Analyst - Institutional Research

If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:
 

Grade: Professional 310

Pay Range: $88,300.00 - $132,400.00

Job Description

Job Profile Summary

The Institutional Analytics and Research (IAR) team supports and enables most WGU teams, departments, and colleges to make data-informed decisions that lead to better student outcomes. Our analysts, scientists, researchers, and managers are distributed across several teams: Faculty Experience Analytics, Institutional Research, Learning Analytics, Outreach Analytics, and Student Success Analytics.

Joining the Institutional Research team, the Senior Research Analyst will leverage both qualitative and quantitative research methods to gather data and derive insights, primarily focusing on survey research administered in Qualtrics.

Essential Functions and Responsibilities

• Research Execution: Performs analysis tasks and follows research plans under minimal guidance and supervision. Supports research planning and design, in collaboration with peers and partners (e.g., research scientists).
• Literature Review: Efficiently organizes, critically reads, and clearly synthesizes across findings and limitations.
• Statistical Modeling: Understands and deploys a variety of mathematical models, descriptive statistics, and classification algorithms to make predictions and identify relationships based on limited sets of data.
• Requirements Gathering: Drives the documentation of data, analytics, and research needs in projects of high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty staff, and leaders. Leads the translation of user stories into technical requirements.
• Expectation Management: Sets and manages expectations about research tasks and activities through clear, timely, and effective communication with partners and stakeholders.
• Data Querying & Manipulation: Answers complex business questions requiring extensive knowledge of the university's data assets across several domains and departments. Identifies adequate data sources and data sets to evaluate hypotheses, build forecasts, and support findings of research projects and experiments. Collaborates with Data Engineering to develop complex ETL/ELT processes and data pipelines.
• Data Quality & Troubleshooting: Identifies, investigates, and solves complex data issues, contributing to the accuracy, completeness, consistency, timeliness, and validity of the university's data. Collaborates with Data Engineering and other data & analytics partners to define standards and best practices that increase data quality across the university.
• Data Visualization & Storytelling: Combines data analysis, visualization, and narrative structures to convey information in compelling ways that instigate deliberate action.
• Mentoring: Supports and accelerates other team members' development through constructive feedback and sharing of technical and institutional knowledge.
• Communication: Conveys information effectively to peers, partners, and senior leaders, using a variety of resources and formats (synchronous and asynchronous, verbal and written) such as e-mails, presentations, meetings, and workshops. Defines and owns communication plans for complex projects and programs.
• Knowledge Management & Documentation: Creates and organizes information about processes, projects, operations, data assets, and insights from analyses and research, making it accessible in ways that increase the university's knowledg