We’re looking for a Product Manager, Growth & Analytics to join the Beeper team. You’ll own product execution for our growth initiatives, working directly with Beeper’s leadership team to figure out what makes users stick, what blocks them, and what makes them pay … and then do something about it.
Your instinct is to scope before you build, measure after you ship, and make sure every product has a clear answer at the end. You’re not the kind of PM who waits for someone else to pull the data. You write your own SQL, build your own dashboards, and use what you find to make better decisions. That analytical depth is what sets you apart.
In this role you will:
- 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.
You’ll do well in this role if you:
- 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.
It will help if you:
- 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. For this role, overlap with North American time zones (Eastern preferred) is important, so you can work closely with the leadership team. This