Product Manager

We are looking for an experienced Product Manager who will take full ownership of their product area. This role is about building products based on data — from deep user understanding and discovery to running experiments and making decisions based on their results.

Your decisions will directly impact key product and business metrics.

What you'll be doing

• Owning your product area and driving decisions about its development
• Running discovery: user interviews, behavioral analysis, hypothesis validation
• Shaping and prioritizing the backlog, building the roadmap
• Launching and analyzing A/B tests, making stop / iterate / rollout decisions
• Maintaining product documentation: PRDs, specs, decision logs
• Working with data: forming hypotheses, validating them, monitoring metrics
• Communicating with stakeholders and aligning the team around goals

What's critical for us

• 3+ years of Product Manager experience — with real ownership of a product or area, not just delivery of backlog items
• Expertise in A/B testing — deep understanding and ability to recognize common pitfalls and make well-grounded decisions based on test results
• Strong prioritization skills — hands-on experience with frameworks (RICE, ICE, or similar), ability to balance impact, effort, and uncertainty; capacity to defend your decisions with clear reasoning
• Data-driven mindset — ability to decompose metrics, identify cause-and-effect relationships, and distinguish correlation from causation
• Strong documentation culture — ability to clearly capture decisions, context, and outcomes so the team can return to them later
• High level of ownership — autonomy in your work, willingness to take responsibility for outcomes, and ability to push back on decisions when data suggests otherwise

• English at Intermediate level or higher — sufficient for working with documentation, technical literature, and day-to-day team communication

   

Nice to have

• Experience with recommendation systems, personalization, or ML-driven products

• Understanding of ML models sufficient for meaningful dialogue with a ML team

   

Personal qualities we value

• Analytical thinking and intellectual honesty when working with data
• Structured communication with different types of stakeholders
• Comfort with ambiguity and ability to reduce it
• Intellectual honesty: acknowledging failures and extracting lessons from them
• Proactivity and ability to move things forward without constant oversight