About this role
Salary: £71,000 - 99,000 per year
Requirements: Solid experience in data science or a similar quantitative role, supporting and influencing product teamsSound understanding of experimentation, including statistical power and minimum detectable effect, the distinction between inconclusive results and no effect, the risks of peeking and post-hoc metric selection, and common causes of invalid experimentsStrong proficiency in Python and SQL, with hands-on experience in statistical analysis and experimentationSome exposure to statistical modelling or machine learning techniques such as regression and classificationAbility to define, implement and operationalise product and feature-level metricsExperience working closely with Product Managers and Engineers as a trusted partner, and willingness to support them through tooling, documentation and consistent practicesCritical thinking, including checking whether a result is trustworthy before interpreting itClear written and verbal communication, including the ability to explain statistical reasoning to non-specialists and constructively stand by findings when they are unwelcomeBachelors degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative fieldExperience with challenging metrics, such as sparse conversion, heavy-tailed revenue or slow-to-observe outcomes, is an advantageFamiliarity with variance reduction techniques is an advantageExposure to causal inference methods for situations where randomisation is unavailable is an advantageExperience with SaaS experimentation tools such as Statsig, Eppo or GrowthBook, or with an in-house platform, is an advantageExperience in a high-scale consumer product environment such as a marketplace, e-commerce or travel platform is an advantageInterest in how modern AI tooling can make analysis faster and experimentation more accessible to product teams is an advantage Responsibilities: Design and analyse experiments end to end with the product teams we support, working directly with Product Managers and Engineers who act on the resultsTurn product questions into testable hypotheses with pre-registered primary metrics, appropriate guardrails and an assessment of what available traffic can detect before an experiment startsDefine and instrument feature-level metrics, considering how metric choice affects sensitivity, interpretation and team decisionsInvestigate results by checking assignment integrity, exposure and data quality before drawing conclusions, and diagnose surprising resultsBuild reusable queries, tooling and templates, and apply shared protocols so teams can run experiments faster and with less reworkCommunicate findings clearly to technical and non-technical audiences, including inconclusive and negative results, with recommendationsInvestigate why a change worked and flag when results may not apply to other users, markets or time periodsConduct analysis beyond experiments, including opportunity sizing, funnel and behavioural analysis, and observational measurement when randomisation is not possibleDocument hypotheses, designs, outcomes and decisions so results remain comparable and the organisation can build on what it learnsDevelop expertise in experimentation and causal inference with review and mentorship from senior and principal data scientists Technologies: AISupportLESSMachine LearningPythonSQL More:
We are Tripadvisor Group, connecting people to experiences worth sharing and aiming to be the worlds most trusted source for travel and experiences. Through our brands, technology and capabilities, we connect a global audience with partners through rich content, travel guidance and two-sided marketplaces for experiences, accommodations, restaurants and other travel categories. Our portfolio includes Tripadvisor, Viator and TheFork. At Tripadvisor Experiences, we love data and use it to empower decision-making. In this Data Scientist role on Viators experimentation team, you will work with product teams to assess the impact of changes and help make experimentation easier through reusable tools, clear documentation and consistent practices. You will learn to navigate the distinctive challenges of a travel marketplace, with support from experienced practitioners. We strive to create an accessible and inclusive experience for all candidates.
last updated 40 week of 2026