Lead Product Analyst; Content Supply & Understanding

• The team. Data & Analytics at Scribd brings together Analytics Engineering, Data Science, and Product Analytics to turn fragmented data and inconsistent definitions into trusted foundations, and to build AI-assisted tools that bring reliable intelligence into how teams make decisions
• The role. This role supports Content Supply & Understanding, the team that owns Scribd’s library of more than 400 million documents, which reaches over 250 million monthly active users. The team’s remit covers who contributes the content, how well we understand it, and how it reaches users
• You will report to the Senior Manager, Data Analytics, and work embedded alongside Product, Engineering, Machine Learning, Data Science, and Analytics Engineering partners. The role is open at the Senior and Lead levels, and we will level based on the experience you bring
• At the Senior level you own analytical work streams within a defined area. At the Lead level you also set the measurement strategy for the area, take on the most open-ended problems, and raise the bar for the analysts around you
• Mandate. Make it possible to say with confidence what is in the corpus, where it falls short of what users look for, and whether enrichment is making content easier to find and use, with numbers that stay comparable as content sources, models, and pipelines change
• Core philosophy. A metric definition is a shared artifact. We care about documentation, versioning, and data quality as much as the readout on top, because a number that quietly breaks upstream is worse than no number at all
• Build measurement for content understanding. Define how we measure classification and metadata coverage, accuracy, and the effect of enrichment on discovery and engagement
• Own analytics for content supply and generate insights on where the corpus falls short: size the gap between user demand and the corpus, estimate the value of closing it, and help prioritize where to invest, using the same market sizing, segmentation, and ROI methods applied in go-to-market analysis
• Partner with Product Managers on strategy and roadmap. Translate product bets into success and guardrail metrics, size opportunities, and make trade-offs explicit
• Design and read experiments (A/B tests and other methods) for content-related product changes, from hypothesis through analysis and readout
• Define and maintain the KPIs, metric definitions, and dashboards for the content domain, and work with Analytics Engineering and Data Engineering on instrumentation and data quality so that metrics stay consistent over time
• Investigate discontinuities and anomalies in content data, and separate real changes in user behavior from pipeline, definition, or instrumentation changes
• Use AI-assisted workflows to speed up analysis and reporting, document how results are validated, and keep AI tools grounded as definitions change
• Present findings and recommendations to product, engineering, and executive audiences, including in regular metrics reviews
• At the Lead level: set analytical standards for the area and mentor other analysts

• Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
• 12 weeks paid parental leave
• Short-term/long-term disability plans
• 401k/RSP matching
• Tuition Reimbursement
• Learning & Development programs
• Quarterly stipend for Wellness, Connectivity & Comfort
• Mental Health support & resources
• Free subscription to Scribd + gift memberships for friends & family
• Referral Bonuses
• Book Benefit
• Sabbaticals
• Company wide events
• Team engagement budgets
• Vacation & Personal Days
• Paid Holidays (+ winter break)
• Flexible Sick Time
• Volunteer Day
• Company-wide Diversity, Equity, & Inclusion programs

You are at your best when the question is not yet well formed. You look at an incomplete…