Senior Product Manager, Data/ML

Senior Product Manager, Data/ML

Mentimeter

Stockholm, Sweden

About the role

AI is changing how people create and consume content, and the Insights product area is where Mentimeter turns that shift into an advantage rather than something we retrofit later. It's the area that decides what every one of our users sees, learns and does next, to turn data into something valuable enough to come back for, and in turn drive retention and expansion for our business.

As Senior Product Manager, Data/ML, you'll own the data and ML depth of Insights: the intelligence that turns every interaction into sharper results, insights and recommendations, pulls in context from inside and outside Mentimeter, and gets better the more it's used. With 300 million users' worth of interaction data behind it, the mandate is to turn that into a defensible asset. The data and ML is the means; a system that drives measurable outcomes for users and the business is the end.

This is a senior, hands-on role with a clear mandate. You'll report to the Product Director of Insights: the Director owns the area's place in company strategy and its org shape, while you own the data and ML depth that delivers it. You'll work alongside the other product managers in the area, our Staff Engineers, our Science Lead, the Office of the CTO, and our data platform teams. The exact shape of the teams is still forming, and you'll help shape it.

In your first year, success looks like a clear direction the area is bought into, and the first solid evidence that the system is compounding.

What you'll do

Own the data and ML direction

• Set the data and ML direction for the area and get alignment behind it across product, engineering and leadership.
• Turn raw interaction data into immediately useful, actionable insight for users, at the individual level and aggregated up to the organization, measured by whether people come back and act on it.
• Keep recommendations grounded in science, not just patterns in the data, working closely with our Science Lead to keep what we surface credible and defensible.

Build the intelligence platform, for UI and agents

• Own the platform that generates insights and recommendations: opinionated, grounded in our thought leadership, and built so the rest of the suite can build on top of it.
• Make that intelligence usable two ways at once, surfaced directly in Mentimeter's UI and exposed so our AI companion and external agents can act on it, with a clean separation between the logic and context layer and the experience layer.
• Build the ranking and timing that gets the right insight to the right user at the right moment, getting sharper from what lands.
• Partner with Staff Engineers on the architecture and technical bets: you bring the product judgment and the outcomes the system must serve, they own the technical design.

Make it learn, and prove it

• Define the measurement and experimentation standards the area scales by, so we only scale what shows durable lift against a strong baseline.
• Show, with evidence, how the system's insights and recommendations get sharper over time as it learns from feedback, for example through reinforcement learning.
• Own how we ship AI well: anticipate failure modes, set quality bars, guard against feedback loops that reinforce errors, and roll back cleanly when the model is wrong.
• Make pragmatic calls on when to reach for ML, GenAI or something simpler, proving value before scaling.

What we're looking for

An experienced data/AI product leader

• Several years leading data-driven or ML-backed products end to end, from discovery through rollout, ideally in B2B SaaS.
• Experience with recommendation engines or similar ranking and personalization systems is highly relevant, and familiarity with AI ecosystems and integration patterns such as MCP is a bonus.

You build the data system, not just the surface

• You've shipped data or AI products where the core value is the system itself, and you're comfortable reasoning about pipelines, models, and how data compounds over time.
• You've led shared-capability or platform work where the real win was adoption and alignment across teams, not just shipping features.

Commercially minded and outcome-driven

• You connect product decisions to business outcomes like retention, expansion and durable engagement, and treat data and ML as how you get there, not the point in itself.
• You have a bias for the simplest solution that works, you resist over-engineering, and you have good judgment on when advanced ML or GenAI is worth the trade-off.

Rigorous and AI-native

• Strong on experimentation, with real fluency in A/B testing, incrementality and causal inference.
• Fluent in shipping AI responsibly and well: eval sets, failure modes, and a clear sense of what "good enough" looks like before something goes live.

A leader who multiplies others

• You lead through influence and coaching, make progress in ambiguity through iterative learning and clear decision points, and bring out the best in the people around you.