Research Scientist I

Western Governors University•Raleigh, NC

About The Position

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 406 Pay Range: $95,900.00 - $143,800.00 Job Description The Research Scientist is responsible for the design and execution of research projects, with emphasis on owning the research plan, selecting appropriate methods, and overseeing research execution. They establish and maintain strong relationships with peers and leaders across IAR, Data Engineering, Machine Learning Operations (MLOps), Product Management, Finance, EdTech, and Faculty staff. They deploy a range of mixed (qualitative and quantitative) methods and tools to produce research supporting fact-based decision-making, disseminating findings across the university and the broader scientific community. At WGU Labs, we’re reimagining what learning can be — anywhere, for anyone. Our research explores how technology, including AI-powered learning solutions, can expand access, improve outcomes, and create new pathways to success across the postsecondary education ecosystem. From traditional higher education to emerging models of workforce learning and skills development, we investigate what works and why. We’re seeking a Research Scientist with specialization in learning science, who thrives in a collaborative, fast-paced environment and is passionate about using evidence to drive innovation in learning. In this role, you’ll design, develop, and test solutions that — at scale — have the potential to shape equitable, high-impact learning experiences for diverse learners and contexts. Ideal candidates bring deep curiosity, learning science expertise, methodological rigor, and a belief that research can unlock opportunities for all learners. You’ll join a team that values experimentation, cross-sector collaboration, and the conviction that great research fuels transformative change in education.

Requirements

Foundational learning science principles — cognitive load theory, retrieval practice, spaced learning, transfer of learning
Assessment design — validity/reliability frameworks, formative vs. summative strategies
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.
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 in selecting and deploying methods and techniques to conduct studies, including A/B testing, quasi-experimental, mixed methods, and others.
Ability to perform analysis tasks and follow research plans under minimal guidance and supervision.
Experienced working with qualitative research software (e.g., Recollective, Quirkos).
Proficient and experienced in using tools like Google Scholar and peer-reviewed journals to identify valid and reliable sources of research, using critical thinking, judgment, and reading skills.
Experienced using SQL, Python/R, and Tableau/Power BI in an ML environment, requiring minimal supervision.
Comfortable with common project management methodologies and frameworks (e.g., Waterfall, Agile, SDLC).
Proficient in the MS Office suite, including advanced Excel knowledge.
Proficient in flowchart and diagramming tools like Miro, Visio, Lucidchart, and similar applications.
Knowledge of the university’s most relevant KPIs.
Ability to apply sound judgment, systems-thinking, and analytical skills to assess risks, perform root-cause analyses, and make recommendations that contribute to the achievement of the university’s objectives.
Ability to perform assigned tasks with high levels of autonomy, reliability, and self-direction, with a bias for action.
Manages conflicting and concurrent activities with sporadic support from their leader(s).
Bachelor's Degree in a related discipline
3 years of related experience in Data Analysis, Business Intelligence, Data Science, Statistics, Decision Intelligence, Research, Learning Science, or Behavioral/Cognitive Psychology.
Equivalent relevant experience performing the essential functions of this job may substitute for education degree requirements. Generally, equivalent relevant experience is defined as 1 year of experience for 1 year of education and is the discretion of the hiring manager.

Responsibilities

Drives the documentation of data and research needs in projects of medium/high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty staff, and leaders.
Takes ownership of mid-level research projects as defined by leadership, ensuring alignment with strategic objectives.
Translates user stories into technical requirements and develops effective research plans.
Begins to mentor peers on basic research methods and processes, fostering a collaborative team environment.
Demonstrates the ability to present research findings to internal stakeholders and external audiences.
Sets and manages expectations about research tasks and activities through clear, timely, and effective communication with partners and stakeholders.
Identifies adequate data sources and data sets to evaluate hypotheses, build forecasts, and support findings of research projects.
Collaborates with Data Engineering in the development of the 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.
Conveys information effectively to peers, partners, senior leaders, and as projects require, external audiences, using a variety of resources and formats (synchronous and asynchronous, verbal and written) such as e-mails, presentations, meetings, and workshops.
Is open and responsive to feedback to improve work.
Defines and owns, in collaboration with communications team, as relevant, communication plans for assigned projects.
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 enrichment of the university’s data management platforms (e.g., data dictionaries, catalogs, etc.).
Drives tasks, activities, and small-scale projects with high levels of autonomy, confidence, and collaboration with peers and partners.
Contributes to organizational discussions and activities to build culture and advance strategic direction.
Owns the research plan and executes following systematic and structured approaches that ensure the validity, reliability, and meaningfulness of research findings, while remaining open to necessary adjustments and adaptations as circumstances require.
Organizes and synthesizes across numerous primary and secondary sources of research, highlighting key gaps and findings in the research area.
Selects and deploys a variety of mathematical models, descriptive statistics, and/or classification algorithms to make predictions and identify relationships based on a limited set of data.
Understands and abides by the relevant policies and methods to access, use, transform, store, and delete data in responsible, secure, and compliant ways.
Designs small-scale solutions and collaborates effectively with other technical specialists (e.g., data engineers) in the construction of data products, systems, and applications.
Tracks and reports own progress, dependencies, and challenges diligently.
Works actively in improving own skills and knowledge through internal and external, formal and informal, structured and unstructured learning.
Is a lifelong learner and embodies a growth mindset.
Performs other job-related duties as assigned.