WGU is looking to solve data and analytics needs in projects of medium/high complexity with a student and equity-centered lens, by analyzing large data sets, developing statistical and predictive models, and conveying information in compelling ways that instigate deliberate action.
Requirements
- Advanced SQL proficiency, with experience writing queries and subqueries, modifying data (INSERT, UPDATE, DELETE), creating views, and knowledge of the different join types, filtering, sorting, aggregation, window functions, common table expressions (CTE), and performance tuning.
- Ability to interpret and design models that describe how data relate to one another and to the properties of the real-world entities they represent.
- Familiarized with versioning tools in the context of CI/CD (e.g., Github) and deploys models using the university’s machine learning operations (MLOps) self-service capabilities.
- Highly proficient and experienced in using tools like Tableau and Power BI to present data and information utilizing charts, graphs, and maps, in ways that make it easy to understand trends, patterns, and outliers.
- Experience using Python, R, and/or Natural Language Processing in an ML environment, requiring minimal supervision.
- Skilled at selecting and deploying methods and techniques like A/B Testing.
- Proficient in flowchart and diagramming tools like Miro, Visio, Lucidchart, and similar applications.
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.
- 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.
- 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.
Other
- 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.
- Sets and manages expectations about analytics tasks and activities through clear, timely, and effective communication with partners and stakeholders.
- 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, meeting, and workshops.
- Ability to apply sound judgment, systems-thinking, and analytical skills to assess risks, perform root-cause analyses, make recommendations, and drive decisions that contribute to the achievement of the university’s objectives.
- Ability to perform assigned tasks with high levels of autonomy, reliability, self-direction, and with a bias for action. Manages conflicting and concurrent activities with sporadic support from their leader(s).
