Data Analyst - Outreach Analytics

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: $73,000.00 - $109,400.00

Job Description

The Institutional Analytics and Research (IAR) team supports and enables most university 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.

The IAR 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.

Primary Responsibilities

• Documents data and analytics needs in projects of medium/high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty staff, and leaders.  Translates user stories into technical requirements.
• Sets and manages expectation about analytics tasks and activities through clear, timely, and effective communication with partners and stakeholders.
• Identifies adequate data sources and data sets to evaluate hypotheses and produce forecasts. 
• Collaborates with Data Engineering in the development of 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.
• 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, 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 enrichment of the university’s data management platforms (e.g., data dictionaries, catalogs, etc.).
• Tracks and reports own progress, dependencies, and challenges diligently.
• 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.
• 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.

Minimum Qualifications

• Bachelor’s degree in