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.

Team Introduction:

College Insights Analytics partners closely with academic leaders to deliver insights, models, and strategic guidance that drive student success and support WGU's key results. We specialize in three core areas:

• Closed Loop Analytics - Empowering academic teams to plan, execute, and evaluate initiatives with data-driven tools and models.
• Driver Analytics - Uncovering key factors and opportunities that influence student outcomes, helping leaders make impactful decisions.
• Targets & Trajectories - Supporting academic planning by setting clear, data-informed targets and long-term success trajectories.

We play a critical role in shaping WGU's student success strategies through meaningful analytics and thought partnership.

Primary Responsibilities

Drives the documentation of data and analytics needs in projects of high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty staff, and leaders. Translates of user stories into technical requirements.

Sets and manages expectations about analytics tasks and activities through clear, timely, and effective communication with partners and stakeholders.

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.

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.

Combines data analysis, visualization, and narrative structures to convey information in compelling ways that instigate deliberate action.

Utilizes software, scripts, and algorithms to perform data-related tasks (e.g. importing, cleaning, transforming, analyzing, displaying) without human intervention.

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.

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 knowledge and efficiency.

Writes and interprets technical documentation (e.g., Entity-Relationship, Conceptual, Logical, and Physical data models).

Contributes actively to the development of the university's data management platforms (e.g., data dictionaries, catalogs, etc.).

Supports and accelerates other team members' development through constructive feedback and sharing of technical and institutional knowledge.

Drives tasks, activities, and small-scale projects with high levels of autonomy, confidence, and collaboration with peers and partners.

Tracks and reports own progress, dependencies, and challenges diligently. Breaks down complex goals into concrete tasks and activities.

Works actively to improve own skills and knowledge through internal and external, formal and informal, structured and unstructured learning. Is a lifelong learner and embodies a growth mindset. Stays abreast of innovative developments in their area of work and plays an active role in deploying them at the university.

Understands and abides by the relevant policies and methods to access, use, transform, store, and delete data in responsible, secure, and compliant ways.

Collaborates effectively with other technical specialists (e.g. data engineers) in the construction of data products, systems, and applications.

Performs other job-related duties as assigned.