IAR Senior Data Analyst

Western Governors University•Salt Lake, UT

8d•Onsite

About The Position

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. The Senior Data Analyst on the Learning Program Analytics team will apply rigorous statistical methods and modeling to uncover what's working and what's not, so we can help every student succeed. The Learning Program Analytics Team uses 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. Their focus is to 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.

Requirements

Bachelor's degree in a related field
5+ years of experience in data analytics, applied statistics, institutional research, or a related quantitative field
Advanced proficiency in SQL, Python, and/or R
Experience with descriptive statistics, causal inference, experimental and quasi-experimental design, and forecasting methods
Ability to apply sound judgment, systems-thinking, and root-cause analysis to assess risks and inform recommendations

Nice To Haves

Familiarity with curriculum development, higher education, or learner success analytics
Exposure to data management platforms (e.g. Databricks), GitHub, and analytics documentation standards
An equivalent combination of training, experience, credentials, or accomplishments demonstrating the ability to perform the essential functions of this job may substitute for education degree requirements.

Responsibilities

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 analysts through code reviews and knowledge sharing, contributing to a culture of continuous learning on the team
Operate with a high level of autonomy, tracking own progress, dependencies, and challenges, and breaking down complex goals into concrete tasks