Data Scientist II - Outreach Analytics

Overview

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:
Technical 408 Pay Range: $ - $

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 Analytics, Institutional Research, Curriculum Analytics, Outreach Analytics, and Student Success Analytics.

Data Scientist II

The Data Scientist II is responsible for producing valuable information from very large sets of structured, semi-structured, and unstructured data. They establish and maintain strong relationships with peers and leaders across IAR, Data Engineering, Product Management, Finance, EdTech, and Faculty staff. They utilize statistical models, machine learning, text mining, natural language processing, and other methods to create predictive models. These models may be integrated into new or existing workflows

• Documents 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. Translates 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 and produce forecasts.
• Analyzes large data sets from both structured and unstructured sources and develops statistical and predictive models.
• 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.
• Collaborates with Data Engineering and other data & analytics partners to define standards and best practices that increase data quality across the university.
• Utilizes software, scripts, and algorithms to perform complex data-related tasks (e.g., importing, cleaning, transforming, analyzing, displaying) without human intervention.
• Combines data analysis, visualization, and narrative structures to convey information in compelling ways that instigate deliberate action.
• 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…