Senior Product Manager II – Commerce and Personalization

The Walt Disney Company

Senior Product Manager overseeing personalization strategies across Disney’s streaming services and product portfolio. Collaborating with various teams to enhance subscriber engagement and product performance.

Posted 6/12/2026full-timeSan Francisco • California, New York • 🇺🇸 United StatesSenior💰 $170,500 - $228,600 per yearWebsite

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

7+ 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.

Benefits

Comp & perks

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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

product managementmachine learningA/B testingexperimentation frameworkspropensity modelsrecommender systemsranking algorithmsdata pipelinesstatistical significancedata-driven decision-making

Soft Skills

cross-functional leadershipstakeholder managementclear communicationinfluence without authorityconsensus buildingstrategic thinkingproblem-solvingadaptabilitypresentation skillswriting strategy documents