Lead Research Analyst - Insittutional 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:
 

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 Lead Research Analyst will drive much of our internal research agenda. Leveraging both qualitative and quantitative methods, they will be responsible for the design and execution of research projects. They will deploy a range of methods and tools to deliver strategic insights and will serve as consultants to various partners across the institution.

Essential Functions and Responsibilities

• Drive our internal research agenda, utilizing both qualitative and quantitative methods, with high levels of autonomy, confidence, and collaboration with peers
• Owns and manages our Qualtrics ecosystem
• Manages relationships with various departments and partners, setting expectations, timelines, scope, and communicating updates
• Working with key stakeholders, within IAR and beyond, builds survey instruments for a variety of strategic projects
• Collaborates with Data Engineering, Salesforce Admins, and other data & analytics partners to define standards, definitions, and efficient data flow from and to our warehouse and systems
• Requirements Analysis: 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 complex 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 in the development of 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. Participates in the definition of data visualization standards and best practices and promotes their adoption across IAR and the university.
• Workflow & Automation: Utilizes software, scripts, and algorithms to perform data-related tasks (e.g., importing, cleaning, transforming, analyzing, displaying) without human intervention.
• Mentoring: Plays a prominent role in other team members' development through constructive feedback