Description review

Product Data Scientist

Tripadvisor · Poland · back to the listing

HR standards

62/100

needs work

Title ↔ description

84/100

solid

Reads as

Data Scientist

99% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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What the listing never says

  • 21 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

About Tripadvisor

The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP) include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork.

About the Role

At Tripadvisor Experiences, the only thing we love more than travel is data. We slice it, we dice it, and we use it to empower our decision-making.

As a Product Data Scientist, you’ll be the analytical backbone of one or more product pods. You’ll own measurement and reporting, support experimentation, and surface the insights that drive product decisions — while actively developing your skills in more advanced analytics methods. This is a role for someone with strong foundational data science skills who is energised by the opportunity to grow.

What You’ll Do

Experimentation

• 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.

Strategic Analysis & Measurement

• 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.’

Stakeholder Management & Communication

• 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.

What You’ll Bring

• 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

Nice to Have

• 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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