Product Data Scientist
RemoteUnited Kingdom
Job Summary
Design and analyze A/B tests across Viator's marketplace, applying sound statistical methods to interpret results and support confident decision-making. Own the measurement framework for your product area by defining key metrics, building instrumentation, and surfacing insights that move the needle. Conduct exploratory analyses using tree-based or regression modeling to inform product decisions, translating outputs into actionable recommendations for the next sprint. Act as a thought partner with product managers and engineers to ensure rigorous analysis, championing unbiased insights even when data contradicts stakeholder hypotheses. This role empowers decision-making at Tripadvisor Experiences, leveraging data to connect global audiences with travel experiences and partners.
Required Qualifications
- Several years in a data science, analytics, or quantitative research role at a data-driven organization
- Advanced SQL skills and hands-on experience querying and manipulating large datasets
- Proficiency with data visualisation tools (Tableau, Looker or equivalent)
- Experience with the full A/B testing process, from test design to results interpretation
- Some proficiency in Python for analysis, experimentation and exploratory modeling
- A track record of using data insights to influence product or business decisions
- Comfort with ambiguity: you can define a question when it isn't handed to you, and you're energised by incomplete information rather than paralysed by it
- A growth mindset: you're actively upskilling in more advanced analytics methods and always willing to learn new tools and techniques
Desired Qualifications
- Exposure to more advanced statistical methods and causal inference techniques — e.g. propensity scoring, synthetic controls, difference-in-differences, Bayesian approaches
- Familiarity with LLMs or NLP tooling for analytics use cases (e.g., content classification, dataset enrichment)
- Experience in travel or e-commerce; understanding of two-sided marketplace dynamics, geo-based demand variation, or supplier/consumer trade-offs
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