Fast Facts

WGU is seeking a Director of Data Science to lead a team in developing AI/ML-powered models to enhance decision-making in academic processes, ultimately fostering a more efficient and personalized academic experience.

Responsibilities: The Director will develop analytics strategies, lead the design and deployment of machine learning models, and mentor a team while collaborating with various stakeholders to improve faculty decision-making processes.

Skills: Deep expertise in applied machine learning, statistical modeling, advanced proficiency in Python and SQL, and strong communication skills to engage diverse teams.

Qualifications: Master's degree in a related field and 10+ years of experience in data analytics or science roles, including 5+ years in leadership positions.

Location: Salt Lake City Office, United States of America

Compensation: $163200 - $293800 / Annually

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: Management_Executive 612Pay Range: $163,200.00 - $293,800.00

Job Description

The Director, Data Science leads a team of data scientists and analysts to develop AI/ML-powered models that drive real-time decision-making in faculty workflows. This role focuses on reducing manual effort and “administrivia” in academic processes by supporting building and implementing predictive and prescriptive systems to provide personalized interventions, enabling faculty to act with precision and efficiency, while reducing “decision fatigue”.

This position plays a critical role in building WGU’s Decision Intelligence capability and will serve as a thought partner and subject matter expert in the integration of machine learning models into university operations. With WGU’s recent adoption of the Decision Intelligence platform, this leader will work to unlock its potential and drive automation and simulation-based decision-making across the academic experience.

The Director partners with stakeholders across Academic Delivery, Schools, Product, MLOps, and other teams to ensure solutions are not only accurate but embedded into the systems faculty and students use daily. This role is responsible for shaping the vision of AI-driven decision support, leading technical development, and ensuring continuous learning through faculty feedback loops.

Primary Responsibilities

• Develops and implements an integrated analytics strategy, including decision models, simulations, and recommender systems, to enhance faculty decision-making, reduce decision fatigue, and support personalized academic journeys, while aligning with institutional goals and stakeholder needs.
• Owns a strategic roadmap for applying AI/ML and simulation-based tools to support continuous improvement of decision intelligence recommendations that support faculty and other student-facing roles and reduce administrative burden.
• Translates institutional priorities into intelligent systems that anticipate faculty needs and streamline outreach to students.
• Acts as a thought leader in applied AI, shaping how emerging technologies are leveraged to enable data-informed actions across academic operations.
• Collaborates with business partners to define and track objectives and success metrics that assess the real-world impact of model recommendations on faculty productivity and student outcomes.
• Leads the design, development, and production deployment of machine learning models that support timely and personalized faculty interventions.
• Coordinates with product, engineering, and analytics teams to ensure model outputs are dynamically integrated into other products, tools, or algorithms that depend on real-time data and recommendations.
• Partners with Product, Business, and MLOps teams to embed models into tools and workflows that reduce the need for manual dashboard review and drive efficient, data-backed actions. Ensures that models are up and running when integrated into workflows.
• Partners with faculty and operational teams to capture behavioral data and feedback on model-driven decisions, enabling continuous model refinement and performance improvement.
• Leads, mentors, and develops a high-performing team of data scientists and analysts, cultivating technical excellence and ownership. Actively attracts, retains, and develops top talent to ensure long-term team strength and capability.
• Fosters a culture of experimentation, delivery, and collaboration that balances cutting-edge innovation with business value.
• Works closely with other analytics and data teams to share knowledge and maintain alignment on best practices and institutional goals.
• Serves as a proactive partner to Product, Business, and Engineering counterparts, helping define opportunities where data science can enable smarter, faster decisions.
• Sets and manages expectations on timelines, technical feasibility, and trade-offs—ensuring transparency while maintaining focus on delivery.
• Engages non-technical stakeholders with clarity and insight, translating complex solutions into actionable ideas and facilitating adoption.
• Identifies key data requirements to support model development and insight generation, aligned to high-impact business problems.
• Collaborates with Data Engineering to ensure pipelines and instrumentation are in place to capture the right data at the right time, at the right quality.
• Works with internal and external partners to augment datasets as needed and ensure relevant data is accessible within shared platforms.
• Keeps stakeholders consistently informed about project goals, timelines, milestones, and risks through clear, concise, and timely updates.
• Adjusts messaging and presentation style based on the audience, translating complex technical concepts into accessible insights for non-technical partners.
• Collaborates closely with other analytics, data science, engineering, and product teams to ensure alignment, share knowledge, and coordinate delivery across interconnected initiatives.
• Stays at the forefront of trends in machine learning, applied AI, and educational analytics, evaluating new methods that can improve how decisions are supported.
• Leads experimentation efforts to test, iterate, and improve models and user experiences, ensuring tools evolve alongside faculty needs.
• Encourages curiosity, creativity, and long-term thinking in how the team approaches complex academic and operational challenges.
• Performs other job-related duties as assigned.

This job description includes a general representation of job requirements rather than a comprehensive inventory of all required responsibilities or work activities. The contents of this document or related job requirements may change at any time with or without notice.

Qualifications

Knowledge, Skills, and Abilities

• Deep expertise in applied machine learning, statistical modeling, and simulations, with hands-on experience deploying models in production environments to drive real-time decision support and automation.
• Advanced proficiency in Python and SQL, with strong working knowledge of cloud-based data platforms and familiarity with MLOps practices for model deployment and maintenance.
• Strong background in predictive modeling, natural language processing (NLP), and experimentation methods.
• Demonstrated ability to design and lead data science initiatives at the intersection of analytics, product, and engineering, translating complex challenges into scalable solutions.
• Proven experience building and leading high-performing, cross-functional teams; capable of guiding teams through change, scaling operations, and cultivating a culture of innovation and accountability.
• Track record of developing and executing forward-looking analytics strategies aligned with institutional priorities, including driving adoption of AI-driven systems and tools.
• Strong project management skills, with the ability to oversee multiple complex initiatives and ensure high-quality delivery within scope and timelines.
• Skilled in navigating organizational complexity and leading large-scale transformation initiatives related to data systems, team structures, and institutional processes.
• Excellent communication and interpersonal skills, with the ability to engage and influence senior leaders, collaborate across technical and non-technical teams, and foster data literacy.
• Experience managing budgets, vendor relationships, and resource allocation to ensure cost-effective delivery and alignment with business value.

Education          

• Master's degree in a related field (data science, analytics, computer science, etc.).

Experience

• 10+ years of experience in data analytics, data science, or a related field.
• 5+ years in leadership roles overseeing large, cross-functional teams.
• Extensive experience collaborating with product and data engineering teams.

Experience in lieu of education

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.

Preferred Qualifications

• 3+ years managing managers.
• Experience managing large budgets, including oversight of vendor contracts and resource allocation for analytics initiatives.
• Strong understanding of decision intelligence principles and platforms.

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Position & Application Details

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.

Additional Information

Disclaimer: The job posting highlights the most critical responsibilities and requirements of the job. It’s not all-inclusive.

Accommodations: Applicants with disabilities who require assistance or accommodation during the application or interview process should contact our Talent Acquisition team at [email protected].

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