Senior Product Manager - Experimentation science

At , data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you make. The journeys you take. The sights you see. And the food you sample.

Through our products, partners and people, we make it easier for everyone to experience the world.

• This role is based in Amsterdam
• At  we are proud of the way we use data and experimentation to drive better product decisions. Over the last 20 years, we have continuously invested in building the best possible experimentation platform to enable our colleagues throughout the company to make the best possible decisions for our customers, partners and our business.

We are seeking a Senior Product Manager to join our Metrics team in the Experimentation Platform team
. The Metrics Team provides the foundational platform for the company’s experimentation ecosystem, enabling product teams to self-sufficiently create, compute, and manage high-quality metrics. We define best practices, maintain scalable pipelines, and deliver tools for metric creation and governance. Ultimately, our work empowers the entire organization to make faster, trustworthy, and data-driven decisions through a robust and extensible framework.

As a Senior Product Manager in the Metrics Team, you will drive the strategy and execution of products that ensure experimentation metrics are statistically rigorous, reliable, and accessible across the company. You will partner with engineers, data scientists, and experimenters to embed advanced methodologies, recommend appropriate metrics, and implement governance practices that safeguard decision-making. Your work will directly shape how teams trust, interpret, and act upon metrics, enabling data-driven decisions at scale.

• Own and set the Metrics Ecosystem Strategy:
  Develop and champion a long-term product vision and roadmap for the experimentation metrics platform, ensuring it meets the company's evolving needs for scale and statistical rigor. Own and define objectives at team and track level.
• Gather stakeholders’ key requirements and incorporate their feedback; manage expectations independently with clear updates provided up to Director level.
• Lead Governance & Best Practices:
  Define and drive the adoption of a unified framework for the entire metric lifecycle, from creation and metadata management to deprecation, ensuring trust and consistency across the organization.
• Guide Experimenters:
  Provide recommendations to experimenters on selecting appropriate, high-quality metrics that ensure meaningful and trustworthy results.
• Harm Protection Governance:
  Define and enforce governance practices that safeguard against harmful or misleading metric use in experimentation.
• Develop Enabling Tools:
  Guide the development of self-service tools, APIs, and infrastructure that empower product teams to create, manage, and analyze their own metrics with confidence and ease.
• Drive Technical Excellence:
  Partner with engineering and data science to design and deliver robust, scalable data pipelines and systems that form the backbone of our experimentation results. Understand the most critical elements of the technical solution, and recognize how multiple systems interrelate to anticipate complex problems or edge cases.
• Ensure Statistical Integrity:
  Be the product authority on statistical methods, ensuring results are accurate, reproducible, and easy to interpret.
• Champion Data Accessibility:
  Ensure metric data and experiment results are accessible, actionable, and integrated into downstream workflows.
• Deliver Critical Projects:
  Navigate complexity and ambiguity to deliver business-critical platform improvements that enhance the reliability and extensibility of our experimentation capabilities. Identify risks and dependencies across multiple areas, and plan for mitigations.
• Actively contribute to the PM communities outside of their team and organization, by facilitating training, learning sessions or contributing to Product Craft working groups.

• Experience:
  
  Proven track record (6+ years) in Product Management, with experience working on complex platforms or data products (e.g., Experimentation, Machine learning platforms).
• Experimentation Fluency:
  Deep understanding of experimentation frameworks and statistical methods with the ability to define, align, and drive adoption of company-wide best practices.
• Statistical Methods:
  Understanding of advanced experimentation methodologies (e.g., sequential testing, quantile testing, ratio metrics, heterogeneous treatment effects) and ability to partner with data scientists to integrate these into scalable tools.
• Experimenter Enablement:
  Experience working directly with product teams and experimenters to guide metric selection, communicate governance policies, and ensure trust in…