WGU is looking to solve the problem of making data-informed decisions that lead to better student outcomes by hiring a Senior Research Scientist to support and enable university teams, departments, and colleges.
Requirements
- 7 years of related experience in Data Analysis, Business Intelligence, Data Science, Statistics, Decision Intelligence, Research, Learning Science, or Behavioral/Cognitive Psychology.
- Experience in lieu of education: 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.
- Writes and interprets technical documentation (e.g., Entity-Relationship, Conceptual, Logical, and Physical data models).
- Designs medium-scale solutions and collaborates effectively with other technical specialists (e.g., data engineers) in the construction of data products, systems, and applications.
- Understands and abides by the relevant policies and methods to access, use, transform, store, and delete data in responsible, secure, and compliant ways.
- Identifies data security risks when dealing with concrete data sets and takes adequate mitigation actions.
- Plays a leading role in the continuous improvement of the university’s data management platforms (e.g., data dictionaries, catalogs, etc.), collaborating with Data Engineering and other data and analytics teams.
Responsibilities
- Drives the documentation of data 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.
- Leads the translation of user stories into technical requirements.
- Drives strategic research contributions and leads large-scale, cross-functional initiatives.
- Identifies adequate data sources and data sets to evaluate hypotheses, build forecasts, and support findings of research projects and experiments. Answers complex business questions requiring extensive knowledge of the university’s data assets across several domains and departments.
- 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.
- Combines data analysis, visualization, and narrative structures to convey information in compelling ways that instigate deliberate action.
Other
- Mentors team members by creating professional development opportunities and providing ongoing coaching.
- Influences institutional decision-making by aligning research outcomes with strategic goals.
- Disseminates findings through professional conferences, external publications, and internal presentations to enhance the institution’s reputation.
- Sets and manages expectations about complex research tasks and activities through clear, timely, and effective communication with partners and stakeholders.
- Plays a prominent role in other team members’ development through constructive feedback and sharing of technical and institutional knowledge.
