Principal Product Mgr

5014 Disney Entertainment & Sports LLC; California (MO); On-site; USD 206,000 - 277,000; Full time

Job summary

Disney Entertainment & ESPN Product & Technology in San Francisco, CA seeks a Senior Product Manager to lead personalization across Disney+, Hulu, ESPN, and related services. You will partner with ML Engineering and Data Science to advance recommender and offer strategies across subscriber journeys, balancing experimentation and ROI.

The role requires 10+ years of PM experience with proven ML collaboration, A/B testing, and monetization expertise in fast-paced environments.

Qualifications

• Extensive experience shipping consumer technology products at scale.
• Strong collaboration with Data Science/ML Engineering to deploy production ML models.
• Deep knowledge of experimentation, measurement, and incrementality.
• Experience with subscription businesses and monetization strategies.
• Data-driven decision making with clear success metrics.

Responsibilities

• Own personalization platform strategy and roadmap across multiple surfaces.
• Define North Star metrics and socialize success criteria for experiments.
• Partner with ML/Data Science to translate business problems into model requirements.
• Build and launch propensity models and cross-surface offer orchestration.
• Design and run scalable A/B tests with measurable LTV impact.
• Ensure model quality with robust data pipelines and responsible holdout design.
• Coordinate with product, data science, analytics, and marketing teams.
• Present updates and strategy memos to leadership.
• Drive ROI-focused prioritization and experimentation frameworks.

Skills

10+ years PM experience

Data Science/ML collaboration

A/B testing expertise

Subscription monetization

Data-driven decision making

Cross-functional leadership

Stakeholder management

Clear communicator

Fast-paced environments

Education

Bachelor's degree in Computer Science, Information Systems, or related field

Tools

Metaflow

Kubeflow

Job description

Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more all working to build and advance the technological backbone for Disney’s media business globally.

We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

These products and brands and the unmatched stories, storytellers, and events they carry matter to millions of people globally.

Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Product Management is responsible for driving the overall user experience, feature strategies and concepts, and engagement paradigms for Disney Entertainment & ESPN's global portfolio of consumer-facing streaming and digital products including Disney+, Hulu, ESPN, ABC, ABC News, Nat Geo, Marvel, and Star Wars.

Team Description

The Commerce Product team is responsible for the subscriber journey across our streaming portfolio - including Disney+, Hulu, and ESPN. We own acquisition, monetization, retention, and lifecycle experiences that serve millions of subscribers globally. Within Commerce, the Commerce Personalization team owns our ML-powered decisioning engine that personalizes offers, promotions, and recommendations across multiple subscriber touchpoints throughout the user journey. This role will drive strategy and execution of our unified commerce personalization engine across the full user journey. You'll partner closely with ML Engineering, Data Science, product, and Analytics teams to drive a three-track roadmap: model improvements, data expansion, and surface experiments.

What You’ll Do

• Own personalization platform strategy and roadmap: Drive three parallel workstreams (model improvements, data expansion, surface experiments) to maximize subscriber lifetime value across key Commerce touchpoints
• Define and socialize North Star metrics: Establish success criteria for all personalization experiments; ensure consistent measurement across surfaces
• Partner with ML/Data Science to build better models: Translate business problems into model requirements and success criteria
• Build new personalization capabilities: Spec and launch propensity models, cross-surface offer orchestration (decide where to show offers, not just what), and unauthenticated personalization
• Design and ship high-impact experiments: Run A/B tests across surfaces with clear LTV success criteria and guardrails (retention, revenue, and engagement)
• Ensure model quality and rigor: Establish randomization infrastructure, LTV-native model training, unbiased training data pipelines, and holdout groups
• Coordinate cross-functionally without direct authority: Align with product, data science, analytics, and lifecycle/marketing teams on shared goals and experimentation frameworks
• Prioritize investment based on ROI: Determine trade-offs between model improvements vs. surface expansion using LTV impact data
• Communicate strategy and results to leadership: Present regular updates and business reviews on portfolio impact; write strategy memos with hypothesis-driven framing and validation gates

Required Qualifications & Skills

• 10+ years of product management experience shipping consumer products at scale (millions of users)
• Proven track record partnering with Data Science/ML Engineering to build and ship production ML models (recommender systems, propensity models, ranking algorithms, personalization platforms)
• Deep understanding of A/B testing, experimentation frameworks, holdout design, statistical significance, and measuring incrementality
• Experience with subscription businesses, pricing, promotions, lifecycle optimization, growth, or monetization
• Data-driven decision-making: comfortable defining success metrics, interpreting experiment results, making go/no-go decisions based on data
• Cross-functional leadership: ability to influence ML Engineering, Data Science, and surface PMs without direct authority; skilled at building consensus across competing priorities
• Strong stakeholder management
• Clear communicator: translates complex ML concepts into business language and vice versa; writes crisp strategy documents and presents effectively to leadership
• Experience working in fast-paced, high-growth environments with ambiguous problem spaces

Preferred Qualifications

• Experience with ML serving infrastructure and personalization platforms (Metaflow, Kubeflow, or similar)
• Built recommendation or ranking systems at scale for complex, multi-SKU product surfaces
• Worked with prediction models to evaluate experiments or prioritize product investments
• Experience coordinating personalization across multiple surfaces to ensure consistent messaging and avoid signal cannibalization
• Background at companies with mature personalization and experimentation cultures (streaming, subscription, e-commerce, or similar)
• SQL proficiency: can write queries to pull experiment data, validate model outputs, and debug attribution issues
• Understanding of ML model constraints: online vs. offline models, training data bias, model architecture trade-offs, feature engineering
• Experience leading cross-functional initiatives in matrixed organizations that required influencing without direct authority
• Track record of defining and shipping challenger models or model improvements that drove measurable business impact

Required Education

• Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, Business, Economics, Statistics, or comparable field of study, and/or equivalent work experience

Employment Type: Full time

Location: San Francisco, CA, USA

The hiring range for this position in San Francisco, CA is $206,400 - $276,700 per year.

A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.