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Lead Product Analyst

Scribd, Inc.
Toronto, CAN
Full-time
Senior
Onsite
Discovered 1 weeks ago
Product analyticsSQLA/B testingKPI and metric definitionData qualityMarket sizing

Full Job Posting

About Scribd

Scribd, Slideshare, Everand, and Fable serve readers and learners around the world.

The company describes a culture emphasizing goals, results, innovation, teamwork, customer focus, and employee flexibility.

Scribd Flex supports employee choice of workstyle and location while requiring occasional in-person attendance for all employees.

Team and role

Data & Analytics includes Analytics Engineering, Data Science, and Product Analytics, building trusted data foundations and AI-assisted decision tools.

The role supports Content Supply & Understanding, responsible for a library of more than 400 million documents reaching over 250 million monthly active users.

The analyst works with Product, Engineering, Machine Learning, Data Science, and Analytics Engineering, reporting to the Senior Manager, Data Analytics.

The posting is open at Senior and Lead levels. Senior analysts own workstreams in a defined area; Lead analysts also set measurement strategy, handle open-ended problems, and support analyst development.

The mandate is to measure corpus contents and gaps, and determine whether enrichment improves content discovery and use, with comparable metrics as sources, models, and pipelines change.

Metric definitions are shared artifacts; documentation, versioning, and data quality matter alongside reporting.

What the role calls for

  • Able to make sense of poorly defined questions, identify what matters, and deliver actionable answers while stating evidence limitations.
  • Comfortable sizing opportunities, modeling returns, writing SQL for metrics, and defending analysis to product and executive leaders.
  • Investigates sharp metric movements for upstream field or pipeline changes before drawing conclusions.
  • Pragmatic about next steps and uses AI where it creates measurable value.
  • Communicates plainly and early; treats methodology and metric documentation as part of the deliverable.

Responsibilities

  • Measure content classification and metadata coverage and accuracy, and assess enrichment effects on discovery and engagement.
  • Analyze content supply, quantify gaps between user demand and the corpus, estimate the value of closing gaps, and help prioritize investment.
  • Partner with Product Managers on strategy and roadmaps; translate product bets into success and guardrail metrics and clarify trade-offs.
  • Design and analyze experiments, including A/B tests, for content-related product changes from hypothesis through readout.
  • Define and maintain domain KPIs, metric definitions, and dashboards.
  • Partner with Analytics Engineering and Data Engineering on instrumentation and data quality so metrics remain consistent over time.

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