Director, Decision Science AI​/ML Engineering & Ops

Director, Decision Science AI/ML Engineering & Ops

Job
Location Burbank, California, United States / Lake Buena Vista, Florida, United States
Business The Walt Disney Company (Corporate)
Date posted May 29, 2026

Do you thrive on transforming complex science into robust, scalable software? Are you driven to advance the platforms and tools that empower scientists to do their best work faster? Are you energized about building the capabilities that allow data scientists to move from "proof-of-concept" to "global production" with the push of a button? We are looking for a visionary leader to bridge the gap between world‑class decision science and industrial‑scale engineering.

The Disney Decision Science and Integration (DDSI) team is the engine behind science‑driven decision‑making across The Walt Disney Company. We leverage advanced algorithms and scientific approaches such as optimization, machine learning, simulation, statistical modelling, genAI and beyond within innovative SaaS products that shape business decisions. We support client areas including Disney Entertainment, Disney Experiences, Corporate Finance, and others.

• Team Vision – Develop and maintain a vision for the team, foster high‑performing AI/ML engineers, and drive a culture of excellence and collaboration.
• MLOps Strategy & Capability Oversight – Define and execute a comprehensive MLOps roadmap, architect repeatable practices across projects, including automated model sustainment, monitoring and governance.
• Strategic Leadership – Manage a high‑performing team, act as the technical translator between science and technology, and shape hiring strategy.
• Reusable Building Blocks Creation – Design, build, and champion a library of configurable, reusable components such as feature engineering modules and model templates.
• Design Pattern Definitions – Develop roadmaps for reusable capabilities, tools and agents, ensuring robust guardrails and adaptive solution design.
• Productisation & Service Design – Partner with Decision Science Delivery to engineer scalable batch and/or callable science services.
• Operational Excellence – Champion metrics and KPI dashboards, implement rigorous automated testing, and establish a "Production First" culture.
• Technical Debt & Modernisation – Identify and remediate technical debt, balancing velocity with stability.
• System Maintenance Stewardship & Operational Reliability – Collaborate with scientists to respond to failures, implement fixes, and ensure model explainability.
• Champion AI‑Powered Productivity – Lead adoption of AI tools within the development process and provide documentation and training.
• Cross‑Functional Partnership – Serve as primary partner for Delivery and collaborate with Decision Science Technology leaders.
• Demand Management & Portfolio Prioritisation – Establish intake mechanisms that maximise reuse and enterprise value.
• Change Management – Connect partners with process improvements and industry best practices.
• Stewardship – Embed security, privacy, explainability and Responsible AI principles, and partner on compliance and cost awareness.
• Communication Agility & Influence – Operate at all organisational levels, demonstrating strong interpersonal and consulting skills.

• 12+ years of related experience
• Prior experience leading decision scientists and/or machine learning engineers to deploy production solutions
• Statistical and modelling fluency for partnership with decision scientists
• Experience with Python, R, SQL
• Experience designing and implementing complex algorithms under performance constraints
• Experience with supervised, unsupervised, reinforcement learning, forecasting, estimation, optimisation and simulation techniques
• Ability to learn technical methods and tools independently
• Leadership strength in navigation of complex organisational dynamics
• Experience with software development tools (Git Lab/Git Hub, Docker, CI/CD)

• Experience with genAI capability development
• Cloud computing concepts including auto‑scaling and AWS services
• Familiarity with emergent design patterns such as agent‑driven solutions and…