Staff Product Manager - Personalization & Recommendations

Job Description

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We are seeking a highly skilled and motivated Staff Product Manager to join our dynamic team and lead the development and enhancement of our personalization services. As a Staff Product Manager, you will play a pivotal role in defining the product strategy, driving innovation, and delivering exceptional user experiences. Your expertise and leadership will guide the direction of our whole page optimization services, ensuring they remain at the forefront of industry trends and customer expectations.
Your efforts will help us scale to >100m customers and become a worldwide top 3 streaming company. You will identify and quantify customer problems, determine approaches to address them, and A/B test different features to solve them. You will be part of a team of Product Managers focused on Personalization, working closely with Software Engineers and Data Scientists.
The team has a diverse range of skill-sets, experience in ML, Recommenders, related fields across streaming media, e-commerce, and other hi-tech problem spaces and hails from top-flight tech firms. You will partner with Editorial and Marketing professionals and discuss your efforts regularly with company executives.
Your Role Accountabilities...
We're seeking a seasoned Staff Product Manager to lead core personalization efforts at WBD. This role is central to our mission to create intelligent, adaptive, and trusted experiences across Max. The ideal candidate has deep experience with ML-driven recommendation or search systems at scale, thrives in complex ecosystems, and is equally fluent in data science, user behavior, and business impact.
As a key contributor for personalization at WBD, you will:
• Define Strategy: Own the end-to-end product strategy for ML-powered personalization and discovery. Identify opportunities that align with WBD's strategic goals and improve engagement, retention, and viewer satisfaction.
• Drive Roadmap: Lead roadmap development for personalization systems, coordinating closely with engineering, data science, UX, and content teams to prioritize initiatives that balance innovation, quality, and speed.
• Evolve the User Experience: Champion user-centricity by leveraging experimentation, user research, and behavioral data to design and optimize personalized experiences across surfaces.
• Orchestrate Systems Thinking: Manage complex ranking systems and feedback loops. Understand how data (user signals, content metadata) flows through algorithms and influences outcomes across product surfaces.
• Stakeholder Leadership: Partner with executives, engineering leaders, data teams, and content strategists to align roadmaps, communicate outcomes, and translate vision into action.
• Benchmark and Differentiate: Monitor trends in personalization, ML tooling, and competitors' discovery experiences to inform roadmap priorities and strategic pivots.
• Measure Impact: Define KPIs that align with both user value and business metrics (e.g., engagement, diversity, relevance). Use experimentation and analytics to optimize performance and guide iteration.
• Launch & Iterate: Lead go-to-market for major personalization capabilities, ensuring internal readiness, high-quality rollout, and learning-based iteration cycles.

Qualifications & Experience...
• 8+ years of product management experience, with significant time spent on ML-driven products or content discovery systems.
• Proven track record of shipping consumer-facing personalization or recommendation systems at scale.
• Strong technical fluency-able to engage meaningfully with engineering and data science on ranking models, data pipelines, and ML evaluation.
• Deep understanding of A/B testing methodologies, statistical analysis, and product experimentation frameworks.
• Systems thinker who can connect the dots between algorithmic performance, UX treatments, and business outcomes.
• Excellent communicator who can synthesize complexity for a range of audiences, from execs to engineers.
• Experience leading cross-functional teams in agile environments; familiarity with tools like Jira and Confluence.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field (preferred but not required).

Championing Inclusion at WBD
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law.
If you're a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.
In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery's total compensation package for employees. Pay Range: $145,600.00 - $270,400.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.
If you're a qualified candidate with an arrest or conviction record, please know that your application will be considered in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Jobcode: Reference SBJ-j667m0-216-73-216-112-42 in your application.