Role overview
Full-Time Regular Positions (classified as regular and working 40 standard weekly hours): This is a full-time, regular position (classified for 40 standard weekly hours) that is eligible for bonuses; medical, dental, vision, telehealth and mental healthcare; health savings account and flexible spending account; basic and voluntary life insurance; disability coverage; accident, critical illness and hospital indemnity supplemental coverages; legal and identity theft coverage; retirement savings plan; wellbeing program; discounted WGU tuition; and flexible paid time off for rest and relaxation with no need for accrual, flexible paid sick time with no need for accrual, 11 paid holidays, and other paid leaves, including up to 12 weeks of parental leave.
How to Apply: If interested, an application will need to be submitted online. Internal WGU employees will need to apply through the internal job board in Workday.
What you'll work on
- Clean, preprocess, and validate data using SQL and Python/R to ensure model inputs are accurate and analysis-ready
- Build predictive models using Python or R, applying machine learning, generative and agentic AI techniques, and advanced statistical techniques
- Analyze course-level performance and identify key trends and equity gaps
- Support experiment design and A/B testing frameworks that assess the impact of interventions and curriculum changes
- Support model monitoring and evaluation efforts, tracking performance over time and flagging unexpected changes
- Collaborate across engineering, product, and program development teams to support data-powered curriculum improvements, including assisting with pipeline development and documentation efforts
- Communicate findings clearly with technical and non-technical stakeholders
What we're looking for
- Familiarity with GitHub, CI/CD pipelines, and MLOps best practices.