Senior Product Manager, Marketplace at Booking Holdings

, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

01 Feb, 26

Salary

0.0

Posted On

03 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Management, Experimentation Frameworks, Statistical Methods, Data Science, Analytical Skills, Communication Skills, Stakeholder Engagement, Technical Fluency, Product Strategy, Delivery Excellence, Leadership, Governance Practices, Metric Lifecycle, Data Accessibility, Experimenter Enablement, Quantitative Skills

Industry

technology;Information and Internet

Description

Role Description We are seeking a Senior Product Manager to join our Metrics team in the Experimentation Platform department. 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. Key Job Responsibilities and Duties Own 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. 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. 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. Role Qualifications and Requirements Experience: Proven track record (6+ years) in Product Management, with experience working on complex platforms / 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 experimentation outcomes. Quantitative and Analytical Skills: Strong quantitative and analytical skills with the ability to translate complex statistical and data concepts into clear product requirements and actionable insights. Communication & Stakeholder Skills: Proven ability to engage, align, and influence stakeholders at all levels and disciplines, from experimenters to C-level, communicating complex data and technical concepts in a clear and actionable way. Technical Fluency: Comfortable working with engineering teams on APIs, data pipelines, and scalable computation systems, with the ability to balance technical constraints with business needs. Product Strategy: Skilled in defining product vision and strategy, setting objectives, and driving alignment across multiple teams and stakeholders. Delivery Excellence: Demonstrated ability to manage roadmaps, prioritize complex dependencies, and deliver high-quality products that scale. Leadership: Ability to work independently, shape long-term product direction, and coach or mentor other PMs when needed. Data Science Background: Prior hands-on experience in data science or statistics roles is preferred. Industry Collaboration & Thought Leadership: Experience engaging with the wider industry through publishing articles, sharing best practices, or bringing industry experts together is preferred. Pre-Employment Screening If your application is successful, your personal data may be used for a pre-employment screening check by a third party as permitted by applicable law. Depending on the vacancy and applicable law, a pre-employment screening may include employment history, education and other information (such as media information) that may be necessary for determining your qualifications and suitability for the position.

Responsibilities

Drive the strategy and execution of products that ensure experimentation metrics are statistically rigorous, reliable, and accessible across the company. Partner with engineers, data scientists, and experimenters to embed advanced methodologies and implement governance practices that safeguard decision-making.