Lead Product Manager, Recommendations

About the role

Scribd, Inc. is seeking a Lead Product Manager to own Scribd's recommendations experience. This role will involve working closely with ML Engineering & Applied Research, Analytics, Data Science, Design, and Machine Learning teams to define and implement strategies that enhance user discovery.

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.