Tripadvisor Group connects people to experiences worth sharing, aiming to be the world's most trusted source for travel and experiences.
Subsidiaries include Tripadvisor, Viator, and TheFork.
Tripadvisor Experiences is the team that builds and supports the world's leading marketplace for travel experiences.
Responsibilities
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.
Requirements
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.
Strong proficiency in SQL and Python, with deep understanding of A/B testing, statistical experimentation, causal inference, and applied experimentation frameworks.
Demonstrated ability to design, diagnose, and improve end-to-end experimentation systems, including governance, tooling, processes, and organisational behaviour.
Strong understanding of product development and decision-making, with ability to influence prioritisation and roadmap decisions through experimentation insight.
Proven ability to influence senior stakeholders across Product, Engineering, and Data organisations without direct authority.
Experience improving experimentation velocity, quality, and adoption through structural interventions such as frameworks, automation, or system redesign.
Strong ability to evaluate experiment design, statistical validity, and interpretation of results, and to improve the thinking of others.
Demonstrated ability to lead through influence, driving behavioural and organisational change across multiple teams.
Exceptional ability to communicate experimentation concepts clearly and confidently to technical and non-technical audiences.
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.
Conditions
Competitive compensation packages, including base salary, annual bonus, and more.