Our four products – Scribd®, Slideshare®, Everand™, and Fable – help billions of people across the globe move beyond access and into insight, application, and expertise. and where every employee is empowered to take action as we prioritize the customer. We believe the best work happens when individual flexibility is balanced with meaningful community connection.

Scribd

Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude.

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. 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 workstreams within a defined area.

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. 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. You can size an opportunity, model its return, write the SQL behind the metric, and defend the number in a room full of product and executive leaders.





When a metric moves sharply, your instinct is to find the field or pipeline that changed before you write the narrative. Build measurement for content understanding. 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.

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. 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 chance 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. A/B test design, hypothesis testing, and statistical analysis.



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.

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. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. In Canada, the reasonably expected salary range is between $152,000 CAD (minimum salary in our lowest geographic market) to $194,000 CAD (maximum salary in our highest geographic market). relevant education or training; In the event that you are considered for a different level, a higher or lower pay range would apply.

This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location.

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 If you apply for a job with Scribd, Inc. or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here. Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas.

Come join us in building something meaningful. #

📌 Lead Product Analyst (Winnipeg)
🏢 Scribd
📍 Winnipeg