Lead Product Analyst

Scribd•San Francisco, CA

1d•Hybrid

About The Position

Scribd, Inc. is seeking a Lead Product Analyst to join their Data & Analytics team, focusing on Content Supply & Understanding. This role supports a library of over 400 million documents reaching over 250 million monthly active users. The team's responsibilities include managing content contributors, understanding content, and ensuring its effective delivery to users. The position reports to the Senior Manager, Data Analytics, and involves close collaboration with Product, Engineering, Machine Learning, Data Science, and Analytics Engineering partners. The role is open at both Senior and Lead levels, with leveling determined by experience. At the Senior level, the focus is on owning analytical workstreams. At the Lead level, responsibilities expand to include setting measurement strategy, tackling complex problems, and mentoring other analysts.

Requirements

4+ years of experience in product analytics or a closely related role for Senior, or 7+ years for Lead, with a record of influencing product or business decisions.
Experience turning ambiguous, loosely defined questions into analysis that changed a decision, in areas where data is sparse or metrics did not yet exist.
Experience with opportunity sizing, segmentation, or business and go-to-market analysis, such as market sizing, pipeline prioritization, or ROI modeling.
Advanced SQL, and experience with Python or R for analysis and statistical work.
Experience with a modern data warehouse such as Databricks, and with BI tools such as Looker or Tableau.
Experience building AI into analytics workflows, such as LLM-assisted querying, analysis, or reporting, to move faster while checking answers against certified metrics or known results.
Working knowledge of experimentation: A/B test design, hypothesis testing, and statistical analysis.
A record of defining a metric, defending it under scrutiny, and revising it when its inputs change.
Experience partnering with Product Managers and Engineers on strategy, roadmap, and measurement.
Strong written and verbal communication, for both technical and non-technical audiences.
Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Economics, or Computer Science, or equivalent practical experience.

Nice To Haves

Experience with content-heavy platforms such as marketplaces, catalogs, publishing, or user-generated content, including supply or content quality analytics.
Experience with classification, taxonomy, or metadata systems, or with search and recommendation, including evaluating ML or LLM outputs against labeled data.
Experience with experimentation platforms such as Statsig.
For Lead candidates: experience mentoring analysts and setting measurement standards for a product area.

Responsibilities

Build measurement for content understanding, defining how to 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, including sizing the gap between user demand and the corpus, estimating the value of closing it, and helping prioritize investment using market sizing, segmentation, and ROI methods.
Partner with Product Managers on strategy and roadmap, translating product bets into success and guardrail metrics, sizing opportunities, and making 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 KPIs, metric definitions, and dashboards for the content domain, and collaborate with Analytics Engineering and Data Engineering on instrumentation and data quality to ensure metric consistency over time.
Investigate discontinuities and anomalies in content data, distinguishing real changes in user behavior from pipeline, definition, or instrumentation changes.
Use AI-assisted workflows to accelerate analysis and reporting, document validation processes, and keep AI tools grounded as definitions evolve.
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.

Benefits

Scribd Flex (flexible work model)
Comprehensive health, dental, and vision coverage
Mental health support and disability coverage
Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
Paid parental leave and family support benefits
Retirement matching and employee equity
Learning and development programs and professional growth opportunities
Wellness and home office stipends
Complimentary access to the Scribd, Inc. suite of products
Enterprise access to leading AI tools