Teams at Scribd, Inc.

Own the acquisition product roadmap and engineering priorities to drive durable user growth. Define target audiences and channel mix, build product-driven acquisition mechanics (referrals, growth loops), enable channel effectiveness (discoverability, search/AI readiness, integrations, tracking), test new acquisition tactics, and align product investment with Performance Marketing, SEO, Partnerships, and Brand while measuring long-term subscriber value.

Lead the recommendations product across candidate generation, ranking, and presentation for Scribd. Define multi-year strategy and metrics, translate retrieval and ranking research into production, run experiments to improve engagement and conversion, partner with ML, engineering, design, and analytics, and communicate roadmap and impact to stakeholders.

Lead and grow a Data Engineering team to build production data pipelines, medallion datasets, and reusable data products. Drive architecture, engineering standards, design reviews, and cross-functional delivery. Partner with Product, Analytics, Data Science, and Platform to enable governed, reliable data foundations for analytics and AI. Mentor engineers and manage multiple concurrent initiatives to deliver predictable outcomes.