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About the Role

The Decision Scientist has a key role within the Experiential Product team and is responsible for developing decision models that support student experiences throughout the lifecycle. This role blends expertise in data science, behavioral/decision science, and data engineering to design, build, monitor, and continuously improve models within the decision intelligence system that trigger recommendations to students, staff, or faculty to drive actions that improve student success. The Decision Scientist collaborates closely with the decision intelligence product lead, technology lead, business SMEs, software and data engineering, ML Ops, and technology architects to build decision products that support personalized student progress and completion, drive automated solutions for operational efficiency and scale, and ensure that decisions are data-informed, equitable, and actionable.

Responsibilities

Build Intelligent Decision Systems: Design, develop, and deploy machine learning models that support key decision points throughout the student lifecycle.
Translate business goals, behavioral objectives, and operational requirements into scalable analytical and machine learning solutions.
Develop decision frameworks that incorporate inputs, alternatives, outcomes, and continuous feedback loops.
Apply advanced analytics, experimentation, and causal inference techniques to identify opportunities that improve student experiences and outcomes.
Partner Across the Organization: Collaborate with business stakeholders to understand critical decisions, success measures, and desired outcomes.
Partner closely with Data Engineering teams to build and maintain the data pipelines and workflows required to support production-ready models.
Communicate findings, recommendations, and model performance to both technical and non-technical audiences.
Operationalize and Scale Machine Learning: Deploy, monitor, retrain, and optimize machine learning models using modern MLOps best practices.
Ensure data inputs, outputs, and model dependencies are properly governed, monitored, and maintained.
Implement model monitoring processes to detect performance degradation, data drift, and operational issues.
Maintain high standards for model reliability, scalability, and production readiness.
Drive Transparency and Responsible AI: Create dashboards, reporting tools, and visualizations that make complex insights accessible and actionable.
Document model assumptions, methodologies, data dependencies, and feedback mechanisms to support transparency and reproducibility.
Ensure models are interpretable, auditable, and aligned with institutional commitments to fairness, accountability, and ethical use of AI.
Perform other duties as assigned.

Requirements

Strong expertise in machine learning, statistical modeling, and predictive analytics, including supervised and unsupervised learning techniques.
Experience selecting, evaluating, and optimizing machine learning models to solve real-world business problems.
Knowledge of modern MLOps practices, including model deployment, monitoring, retraining, CI/CD pipelines, and drift detection.
Experience developing and supporting data pipelines, including data ingestion, transformation, orchestration, and workflow automation.
Ability to model complex decision processes and connect decision outcomes to measurable business objectives.
Experience incorporating behavioral, operational, or customer-focused signals into analytical frameworks.
Proficiency in Python or R and hands-on experience with machine learning frameworks such as: Scikit-learn TensorFlow PyTorch
Experience deploying machine learning solutions in cloud environments such as AWS, Azure, or Google Cloud Platform.
Proficiency with Git, GitHub, and collaborative software development practices.
Excellent communication, collaboration, and stakeholder management skills.
Experience in higher education, student success, healthcare, or another mission-driven environment is preferred.
Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Behavioral Sciences, Mathematics, or a related quantitative discipline.
Master's degree preferred.
Equivalent relevant experience performing the essential functions of this job may substitute for education degree requirements.
5+ years of experience in data science, advanced analytics, decision intelligence, or a related field.
2+ years of experience designing, deploying, and maintaining machine learning solutions in production environments.
Experience building and supporting data pipelines and operational workflows that enable scalable analytics and machine learning capabilities.
Demonstrated success developing decision models, analytical frameworks, or predictive systems that influence human behavior, business outcomes, or customer experiences.

Skills

Machine learning
Statistical modeling
Predictive analytics
Supervised learning
Unsupervised learning
Model deployment
Model monitoring
Model retraining
CI/CD pipelines
Drift detection
Data pipelines
Data ingestion
Data transformation
Orchestration
Workflow automation
Decision modeling
Analytical frameworks
Predictive systems
Python
R
Scikit-learn
TensorFlow
PyTorch
AWS
Azure
Google Cloud Platform
Git
GitHub
Communication
Collaboration
Stakeholder management

Location

Raleigh office, 5 days a week

Work Type

Full-time
Regular

Experience Level

5+ years of experience in data science, advanced analytics, decision intelligence, or a related field
2+ years of experience designing, deploying, and maintaining machine learning solutions in production environments

Education Level

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Behavioral Sciences, Mathematics, or a related quantitative discipline
Master's degree preferred

Salary/Compensations

$118,900.00 - $178,500.00

Benefits

Medical
Dental
Vision
Telehealth and mental healthcare
Health savings account
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
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
Other paid leaves, including up to 12 weeks of parental leave

About the Company

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.
In 1997, a coalition of 19 U.S. governors founded Western Governors University with a singular vision: to make higher education more accessible by offering full degree programs online.
Starting small, we quickly expanded. Today, we’re one of the largest accredited online universities in the U.S.

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to any protected characteristic as required by law.