About this role
About Tripadvisor
The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork.
Tripadvisor Experiences is the team that builds and supports the world's leading marketplace for travel experiences . We believe that making memories is what travel is all about. And with 400,000+ travel experiences to explore—everything from simple tours to extreme adventures (and everything in between) —making memories that will last a lifetime has never been easier.
About the role:
As a Senior Manager, Product Data Science & Experimentation you will own the health, velocity, quality, governance, and organisational maturity of experimentation across Viator and Tripadvisor, while providing strong technical leadership from within the Product Data Science function.
What You’ll Do
You will be responsible for ensuring experimentation is designed, executed, and interpreted in a consistent, high-quality way across the organisation, while driving continuous improvement in velocity, adoption, and organisational capability.
• Own the end-to-end experimentation operating system, including governance, standards, lifecycle, and quality controls across all experiments.
• Define and enforce experimentation standards, ensuring consistent rules for experiment design, metric selection, statistical validity, and metadata completeness.
• Drive experimentation velocity and coverage, ensuring balanced testing across product surfaces and eliminating under-tested or untested areas.
• Establish a single source of truth for experimentation health, ensuring leadership can reliably understand what is being tested, where, and with what outcomes.
• Partner with Product, Engineering, Data Engineering, and Product Data Science leadership to align on priorities, resolve system-level issues, and improve experimentation execution.
• Identify and eliminate systemic failure modes in experimentation design and execution, preventing recurring issues rather than repeatedly fixing them downstream.
• Reduce reliance on central experimentation support by improving upstream experiment design quality and embedding correct behaviours into product teams.
• Own experimentation literacy across the organisation, ensuring teams understand how to design, run, and interpret experiments correctly as part of normal product development.
• Design and scale frameworks, documentation, and tooling that make correct experimentation the default and reduce dependency on reactive support or ad hoc guidance.
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