IAR Senior Data Analyst

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: $91,000.00 - $136,400.00

Job Description

The IAR Senior Data Analyst is responsible for extracting, processing, analyzing, and reporting on data to produce rigorous, actionable insights and research. They establish and maintain strong relationships with peers and leaders across IAR, Data Engineering, Product Management, Finance, EdTech, and Faculty staff. They perform ad hoc analyses, build standard reports and data visualizations, and deliver information and insights through various methods and media that privilege data storytelling and compress time-to-action.

 

IAR Senior Data Analyst

 

Want to use your data skills to improve how thousands of students learn?

At WGU, data drives decision-making, from course design to student support. As a Senior Data Analyst on our Learning Program Analytics team, you'll apply rigorous statistical methods and modeling to uncover what's working and what's not, so we can help every student succeed.

 

About the Learning Program Analytics Team

We use WGU's rich data assets to evaluate the impact of course features and initiatives, identify equity gaps, and drive continuous improvement through advanced statistical analysis. Our focus is clear: bring quantitative rigor and depth to the questions that matter most, using causal inference, impact analysis, and modeling to move beyond describing what happened to understanding why, and what to do next.

 

Senior Data Analyst Role

The IAR Senior Data Analyst is responsible for applying advanced statistical methods, causal inference, and modeling to produce rigorous, actionable insights and research. They establish and maintain strong relationships with peers and leaders across IAR, Program Development, and Academic Delivery. They perform ad hoc analyses and impact evaluations, and deliver information and insights through various methods and media that privilege data storytelling and compress time-to-action.

 

What you'll do

• Design and conduct causal inference and impact analyses to evaluate course features, initiatives, and equity gaps
• Identify appropriate data sources and data sets to evaluate hypotheses and support research and analysis
• Apply advanced statistical methods (e.g., regression, hypothesis testing, experimental and quasi-experimental design) to test hypotheses and surface actionable patterns
• Build statistical and predictive models to bring quantitative depth to course performance questions
• Translate business and academic needs into clear technical and analytical requirements
• Use SQL, Python, and/or R to manage and extract insights from complex, multi-source data environments
• Investigate and resolve data quality issues to ensure the integrity and validity of underlying analyses
• Present findings to cross-functional teams and leadership, adapting to technical and non-technical audiences
• Document methodology, sources, and insight history to support transparency, rigor, and reproducibility
• Understand and apply relevant data governance and security policies to access, use, and store data responsibly
• Collaborate with fellow