Note: The job is a remote job and is open to candidates in USA. Tripadvisor is a leading travel company that connects people to experiences worth sharing. As a Product Data Scientist, you will serve as the analytical backbone of product pods, focusing on measurement, reporting, and insights to drive product decisions while enhancing your skills in advanced analytics methods.
Responsibilities
- Design and analyse A/B tests across Viator’s marketplace, applying sound statistical methods to interpret results and support confident decision-making
- Champion experimentation best practices: power calculations, guardrail metrics, and multiple testing corrections
- Develop your mastery of causal inference and advanced experimentation techniques (e.g., difference-in-differences, propensity scoring, synthetic controls) as you apply them to answer questions that can't be randomized — such as measuring the impact of pricing changes on supplier retention or the long-term effect of personalization on traveler LTV
- Own the measurement framework for your product area: define key metrics, build the instrumentation to track them, and surface insights that move the needle
- Conduct exploratory analyses and deep dives into our data, using various data science approaches, to inform product decisions; for example, using tree-based or regression modeling to identify signals of high LTV
- Enable self-service through scalable datasets, metrics, dashboards and reporting frameworks
- Translate analytical outputs into actionable insights and clear product recommendations: not just ‘here’s the data,’ but ‘here’s what it means for the next sprint and how we should test it.’
- Act as a thought partner with product managers and engineers to ensure the right data questions are being asked
- Translate analyses into clear narratives that are accessible to non-technical audiences — emphasising actionable insights and ‘so what’ over technical detail
- Be a champion of unbiased, rigorous analysis — including when the data doesn’t support a stakeholder’s hypothesis; willingness to be the voice of inconvenient truths is a core expectation of this role
Skills
- Several years in a data science, analytics, or quantitative research role at a data-driven organization; strong product analysts who are actively upskilling in data science methods are encouraged to apply
- 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
- 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
Company Overview