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Salary: USD 153,000 - 216,500 / annual
Scribd is hiring a Product Analyst to own measurement and analytics for the Content Supply & Understanding team, which manages Scribd's library of over 400 million documents reaching 250+ million monthly active users. You will report to the Senior Manager, Data Analytics, and work embedded with Product, Engineering, Machine Learning, Data Science, and Analytics Engineering partners.
In this role, you will build measurement frameworks for content understanding, defining how Scribd measures classification accuracy, metadata coverage, and the impact of enrichment on discovery and engagement. You'll own analytics for content supply, identifying gaps between user demand and the corpus, estimating the value of closing those gaps, and helping prioritize investment using market sizing, segmentation, and ROI methods.
Key responsibilities include:
- Translating product strategy into success and guardrail metrics, sizing opportunities, and making trade-offs explicit
- Designing and analyzing experiments (A/B tests and other methods) for content-related product changes
- Defining and maintaining KPIs, metric definitions, and dashboards for the content domain, working with Analytics Engineering and Data Engineering on instrumentation and data quality
- Investigating anomalies and discontinuities in content data, distinguishing real behavioral changes from pipeline or instrumentation changes
- Leveraging AI-assisted workflows to accelerate analysis and reporting while validating results against certified metrics
- Presenting findings and recommendations to product, engineering, and executive audiences in regular metrics reviews
Scribd operates on a Flex model balancing individual flexibility with intentional in-person collaboration. Occasional in-person attendance is required for all employees.
REQUIREMENTS:
- 4+ years of product analytics or closely related experience with a record of influencing product or business decisions
- Demonstrated ability to turn ambiguous, loosely defined questions into actionable analysis in data-sparse environments where metrics did not yet exist
- Experience with opportunity sizing, segmentation, business analysis, market sizing, pipeline prioritization, or ROI modeling
- Advanced SQL and experience with Python or R for analysis and statistical work
- Experience with modern data warehouses (e.g., Databricks) and BI tools (e.g., Looker, Tableau)
- Experience building AI into analytics workflows (LLM-assisted querying, analysis, reporting) with measured value and validation against certified metrics
- Working knowledge of experimentation: A/B test design, hypothesis testing, and statistical analysis
- Proven track record defining metrics, defending them under scrutiny, and revising when inputs change
- Experience partnering with Product Managers and Engineers on strategy, roadmap, and measurement
- Strong written and verbal communication for technical and non-technical audiences
- Bachelor's degree in a quantitative field (Statistics, Mathematics, Economics, Computer Science) or equivalent practical experience
NICE TO HAVE:
- Experience with content-heavy platforms (marketplaces, catalogs, publishing, user-generated content) including supply or content quality analytics
- Experience with classification, taxonomy, metadata systems, search, or recommendation, including evaluating ML/LLM outputs against labeled data
- Experience with experimentation platforms such as Statsig
