About Tripadvisor
We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences, so we can collectively revolutionize travel and together find the good out there.
Tripadvisor is the world’s largest online travel site, visited by 390 million travellers each month, and our Experiences business, Viator, is a fast-evolving and highly data-driven part of the organisation.
At Viator, data is at the heart of how we build great products. We use it to understand our customers, improve decision-making, and drive measurable business impact.
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.
- Ensure experiment metadata integrity and completeness so that results are comparable, auditable, and usable for decision-making and organisational learning.
- Act as an escalation point for experimentation system health, ensuring issues are resolved quickly and do not persist across cycles.
Skills & Experience
- Experience: Extensive experience in data science, experimentation, product analytics, or a similar quantitative discipline, with a proven track record of improving experimentation systems, governance, or decision-making quality in a product-led organisation.
- Technical Expertise: Strong proficiency in SQL and Python, with deep understanding of A/B testing, statistical experimentation, causal inference, and applied experimentation frameworks.
- Systems Thinking: Demonstrated ability to design, diagnose, and improve end-to-end experimentation systems, including governance, tooling, processes, and organisational behaviour.
- Product Acumen: Strong understanding of product development and decision-making, with ability to influence prioritisation and roadmap decisions through experimentation insight.
- Strategic Influence: Proven ability to influence senior stakeholders across Product, Engineering, and Data organisations without direct authority.
- Scaling Impact: Experience improving experimentation velocity, quality, and adoption through structural interventions such as frameworks, automation, or system redesign.
- Critical Thinking: Strong ability to evaluate experiment design, statistical validity, and interpretation of results, and to improve the thinking of others.
- Leadership: Demonstrated ability to lead through influence, driving behavioural and organisational change across multiple teams.
- Communication: Exceptional ability to communicate experimentation concepts clearly and confidently to technical and non-technical audiences.
You could be an especially great fit if you have:
- Experience improving experimentation systems, governance, or operating models at scale rather than only running or analysing experiments.
- Experience driving experimentation adoption across multiple product teams, domains, or brands.
- Experience building experimentation frameworks, standards, or guardrails that improve quality and consistency.
- Experience reducing organisational dependency on central experimentation or data science teams through better system design and self-service enablement.
- Experience working in high-scale product environments such as marketplaces, e-commerce, or travel platforms.
- Experience working in SaaS experimentation tools such as Statsig, Eppo, Growthbook and others
- A reputation for improving how organisations make decisions, not just the quality of individual analyses or experiments.
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