Product Manager, Growth & Analytics, Beeper

Automattic is a fully-remote company that is looking for a Product Manager, Growth & Analytics to join the Beeper team. The role involves owning product execution for growth initiatives, conducting experiments, and maintaining dashboards to inform leadership about key metrics.

Responsibilities:

• Own the product process for growth. Specs, user stories, success criteria, experiment tracking: you keep it tight so engineering isn’t guessing at scope and leadership isn’t guessing at outcomes
• Run experiments end-to-end. Hypothesis, spec, instrumentation, launch, results. You close the loop every time
• Build and maintain the dashboards leadership relies on. Activation, retention, conversion, engagement: the numbers the team checks every week come from you
• Investigate when metrics move. When activation drops or retention shifts, you’re the person who figures out why and what to do about it
• Work with engineering and support to validate problems and confirm whether what we shipped actually worked
• Keep product documentation current. Feature specs, release notes, internal reference docs: the stuff that keeps a distributed team aligned

Requirements:

• Have four to six years in product management, growth, or a closely related role where you owned product execution
• Have strong SQL skills (CTEs, window functions, cohort analysis, funnel queries). This is a hard requirement, not a nice-to-have
• Have experience with a cloud data warehouse and can build dashboards and recurring queries
• Can write a spec that engineering builds against and a data summary that leadership makes decisions with
• Have run experiments and know the difference between shipping a feature and learning something
• Have experience with experiment design and A/B testing frameworks
• Have worked on a messaging, social, or consumer product
• Are familiar with subscription or freemium business models
• Understand basic statistical methods enough to know when a result is meaningful and when you're fooling yourself with correlation
• Are comfortable working with imperfect data when instrumentation isn't clean
• Bonus points if you've worked on a distributed team or at a startup where you had to be scrappy and self-directed