Lead Product Manager, Recommendations

About this role

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. CULTURE AT SCRIBD, INC. We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location. So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude. This posting reflects an approved, open position within the organization. Lead Product Manager, Recommendations In this role, you'll own Scribd's recommendations experience — helping 200 million monthly visitors discover content they didn't know they were looking for, across a corpus of 300 million documents. You'll work at the intersection of ML and product to surface the right content to the right person, at the right time. Success means defining a compelling vision, crafting metrics that truly matter, and experimenting your way to breakthrough features that redefine discovery — in close partnership with Engineering, Analytics, Data Science, Design, and Machine Learning teams. Responsibilities - Chart the long-term recommendations strategy — own a multi-year roadmap spanning candidate generation, ranking, and results presentation across Scribd's surfaces, guiding every user from interest to the right document - Partner with ML Engineering & Applied Research — translate cutting-edge retrieval and ranking research into production systems that blend collaborative signals, content embeddings, and real-time behavioral data for best-in-class personalization - Define the metrics that matter — establish and monitor leading indicators of recommendations success: engagement rate, click-through, content completion, and downstream subscription conversion and retention - Balance short-term wins with long-term vision — ship incremental relevance improvements that hit revenue goals while building an extensible recommendations platform aligned with Scribd's 3-year AI strategy - Fuse data with the voice of the customer — synthesize experiment results, behavioral analytics, user interviews, and feedback to inform prioritization and feature design - Communicate with clarity and influence — align product, engineering, design, content, and executive stakeholders by clearly articulating requirements, timelines, deliverables, and expected impact Qualifications - 8+ years of product management experience, including 4+ years leading recommendations or search products in a high-traffic consumer environment - Demonstrated success shipping ML-driven features that moved core business metrics (engagement, conversion, or revenue) at scale - Deep familiarity with retrieval and ranking algorithms, embeddings, and feature stores — paired with the ability to reason about end-to-end customer journeys for distinct user segments - Track record of thriving amid ambiguity: shaping a multi-year vision, aligning cross-functional teams, and delivering incremental wins along the way - Exceptional written and verbal communication skills — adept at crafting product briefs and presenting data-backed decisions to senior leadership - Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience) Bonus Points - Hands-on proficiency with AI tools for productivity and analytics — including LLM-powered workflows, SQL copilots, and data exploration tools — to move fast, prototype ideas, and pressure-test assumptions without always needing engineering support - Experience designing LLM- and GenAI-enhanced discovery experiences that go beyond raw recommendations to deliver personalized, task-specific value - Familiarity with modern ML ops tooling ------------------------------------------------------------------------------------------------ At Scribd, Inc., your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States.   In the state of California, the reasonably expected salary range is between $177,000 [minimum salary in our lowest geographic market within California] to $256,000 [maximum salary in our highest geographic market within California].   In the United States, outside of California, the reasonably expected salary range is between $151,000 [minimum salary in our lowest US geographic market outside of California] to $244,000 [maximum salary in our highest US geographic market outside of California].   In Canada, the reasonably expected salary range is between $179,000 CAD[minimum salary in our lowest geographic market] to $228,000 CAD[maximum salary in our highest geographic market].   We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and