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Tripadvisor is seeking a Data Scientist to join the experimentation team supporting Viator, a marketplace for travel experiences. In this role, you will partner with product teams to measure the impact of product changes, define meaningful metrics, and ensure sound decision-making through rigorous experimentation.
Key Responsibilities:
- Design and analyze experiments end-to-end with product teams, working directly with Product Managers and Engineers to translate results into action.
- Convert product questions into testable hypotheses with pre-registered primary metrics, appropriate guardrails, and realistic power assessments before experiments launch.
- Define and instrument feature-level metrics, understanding how metric choice affects sensitivity, interpretation, and team decision-making.
- Investigate results thoroughly by checking assignment integrity, exposure, and data quality before drawing conclusions; treat surprising results as diagnostic puzzles rather than announcements.
- Build reusable queries, tooling, and templates to enable teams to run good experiments faster and with less rework.
- Communicate findings clearly to both technical and non-technical audiences, including inconclusive and negative results, with actionable recommendations.
- Look beyond whether a change worked to understand why it worked, and flag when results may not generalize across users, markets, or time periods.
- Conduct analysis beyond experiments, including opportunity sizing, funnel analysis, behavioral analysis, and observational measurement where randomization isn't possible.
- Document hypotheses, designs, outcomes, and decisions to maintain comparability and compound organizational learning.
- Develop expertise in experimentation and causal inference with mentorship from senior and principal data scientists.
Tripadvisor operates in a unique marketplace context where supply is finite and shared, and customers often book experiences infrequently. You'll learn to navigate complex analytical problems where obvious approaches can yield misleading answers, supported by experienced practitioners.
Requirements:
- Solid experience in data science or similar quantitative role supporting and influencing product teams.
- Sound understanding of experimentation fundamentals: statistical power, minimum detectable effect, the distinction between inconclusive results and no effect, and common sources of experimental invalidity (peeking, post-hoc metric selection, etc.).
- Strong proficiency in Python and SQL with hands-on experience in statistical analysis and experimentation; some exposure to statistical modeling or machine learning (regression, classification).
- Ability to define, implement, and operationalize product and feature-level metrics, with support from senior colleagues on complex cases.
- Experience working closely with Product Managers and Engineers as a trusted partner; willingness to build tooling, documentation, and consistent practices to support teams.
- Critical thinking: habit of assessing result trustworthiness before interpretation; comfort communicating when results are unreliable.
- Clear written and verbal communication; ability to explain statistical reasoning to non-statistical audiences and constructively hold position when results are unwelcome.
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or related quantitative field.
Preferred Qualifications:
- Experience with difficult-to-measure metrics (sparse conversion, heavy-tailed revenue, slow-to-observe outcomes).
- Familiarity with variance reduction techniques and their impact on sensitivity.
- Exposure to causal inference methods for non-randomized settings.
- Experience with SaaS experimentation tools (Statsig, Eppo, GrowthBook) or in-house platforms.
- Background in high-scale consumer product environments (marketplace, e-commerce, travel).
- Interest in how modern AI tooling can accelerate analysis and democratize experimentation.
