Lead Product Manager – AI Research Experiences
Scribd, Inc.
PythonSaltStackSparkSQL
Lead Product Manager – Recommendations and Personalization
Scribd, Inc.
full-time
Posted on:
Origin: • 🇺🇸 United States • California
Visit company websiteSalary
💰 $157,500 - $255,000 per year
Job Level
Senior
Tech Stack
PythonSaltStackSparkSQL
About the role
- Chart the long‑term recommendation & personalization strategy — own a multi‑year roadmap that spans the Scribd homepage, our content graph, and yet to be defined product surfaces, guiding every user to their next must‑read document or knowledge insight.
- Partner with Machine‑Learning Engineering & Applied Research — translate cutting‑edge retrieval and ranking research into production algorithms that blend semantic embeddings, and real‑time behavior for best‑in‑class relevance and trust.
- Define the metrics that matter — establish and monitor the leading indicators of subscription conversion, retention, and lifetime value, using them both to evaluate product success and to feed continuous model‑training loops.
- Balance short‑term wins with long‑term vision — deliver incremental improvements that hit our revenue goals while building an extensible personalization platform aligned with Scribd’s 3‑year AI strategy.
- Fuse data with the voice of the customer — synthesize experiment results, usage analytics, user interviews, and feedback sessions 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 for critical initiatives, securing buy‑in at every stage.
Requirements
- 7+ years of product management experience, including 4+ years leading recommender systems, personalization, or large-scale search/ranking products in a high-traffic consumer environment.
- Demonstrated success shipping ML-driven recommendation features that moved core business metrics (engagement, conversion, or revenue) for large scale products.
- 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, bringing in inputs from multiple teams, 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: Hands-on proficiency with SQL and a scripting language (Python or R) for rapid data exploration, prototyping, and model evaluation.
- Bonus: Experience designing LLM- and GenAI-enhanced user experiences that go beyond raw chat to deliver task-specific value.
- Bonus: Familiarity with modern ML operations tooling—from vector databases to end-to-end model-ops workflows (MLOps / LLMOps).
- Bonus: Passion for the written word and open knowledge.
