---
title: 'Senior Data Scientist, Experimentation at Tripadvisor'
canonical: 'https://feeny.ai/job/senior-data-scientist-experimentation-tripadvisor-london-myrfkddp2es5'
type: 'job'
last_seen: '2026-10-19'
---

# Senior Data Scientist, Experimentation at Tripadvisor

- **Company:** Tripadvisor
- **Location:** London, United Kingdom
- **Posted:** 2026-09-24
- **Last confirmed live:** 2026-10-19
- **Apply:** https://job-boards.greenhouse.io/tripadvisor/jobs/8230405

## Job description

## 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.

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.

What You will do:

As a Senior Data Scientist on our experimentation team you will work across a range of product areas, acting as the partner that Product and Engineering teams rely on to know how to set up and run investigations, whether a change worked and why it worked.

Much of your impact will come from improving how those teams experiment rather than running their experiments for them: the metrics, guidance, tooling and protocols that let them move quickly without sacrificing rigour.

You will also lead the measurement problems a standard A/B test cannot answer, where traffic is limited, users compete for the same supply, or the outcomes that matter take months to appear.

You will:

- Own the experimentation and measurement strategy for your domain, from how questions are framed through to how decisions are made and reviewed.
- Provide the guidance, tooling and protocols that improve your partner teams' experimentation velocity without sacrificing rigour.
- Lead the design of experiments where a standard A/B test is not sufficient, including low-traffic surfaces, users competing for the same supply, long-horizon or censored outcomes, and changes that cannot be cleanly randomised.
- Go beyond whether a change worked to why it worked and whether it generalises across users, markets and time.
- Assess how the decisions your teams make affect platform health and growth, and raise it when short-term wins carry a longer-term cost.
- Define and operationalise the metric framework for your domain, including guardrails and proxies for outcomes that take too long to observe directly.
- Improve the sensitivity of measurement in your area through metric design, variance reduction and better exposure definition, so teams can detect the effects they care about in a realistic timeframe.
- Standardise the recurring analytical and experimentation processes in your domain, using automation and AI capabilities where they improve consistency or save time.
- Influence roadmap and prioritisation through evidence, including advocating against work when the evidence doesn't support it.
- Raise technical quality in the teams you work with by reviewing experiment designs and analyses, and mentoring less experienced data scientists.

Skills & Experience:

- Experience: Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organisation.
- Statistical & Experimentation Expertise: Authoritative command of experimentation in all its forms, from experimental design and variance reduction to causal inference, bandits and Bayesian methods. You should be able to develop and validate methodology, not only apply it.
- Technical & Modelling Expertise: Expert level proficiency in Python and SQL. Deep, hands-on experience with statistical modelling, (quasi) experimentation, multi-arm bandits, and a wide range of machine learning techniques such as regression, classification and clustering.
- Product Acumen: Demonstrated ability to define, implement and operationalise crucial product and feature-level metrics from scratch.
- Partnership & Enablement: Demonstrated ability to improve how other teams work by providing guidance, tooling and protocols, increasing both the speed and the quality of their experimentation rather than absorbing the work yourself.
- Decision Impact & Platform Health: Ability to critically assess how product decisions affect platform health and growth over time, and to bring that perspective into how experiments are designed and interpreted.
- Standardising at Scale: Experience standardising processes, frameworks or methods across multiple teams, including the use of AI and automation to make good practice the default.
- Cross-Functional Partnership: Proven ability to build strong relationships and drive outcomes across Product, Engineering, Data Platform and other central functions, often without direct authority.
- Critical Thinking: Leader in critical thinking, with a demonstrated habit of establishing whether a result is trustworthy before establishing what it means.
- Communication: Exceptional ability to explain measurement, method and uncertainty clearly to technical and non-technical audiences at every level.
- Education: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

You could be an especially great fit if you have:

- Experience with experimentation in a marketplace, where interference between users and shared supply complicate measurement.
- Experience with variance reduction beyond a single pre-period covariate, and a view on what works when the metric of interest is infrequent or heavy-tailed.
- Experience building or validating proxy metrics for long-horizon outcomes.
- Exposure to Bayesian approaches, particularly for low-traffic surfaces or pooling evidence across small markets.
- Experience with SaaS experimentation tools such as Statsig, Eppo or GrowthBook, or with an in-house platform.
- Experience in a high-scale marketplace, e-commerce or travel platform, and familiarity with the seasonality and long purchase cycles that come with them.
- Experience improving experimentation practice at team or organisational level through frameworks, tooling or enablement.
- Experience applying AI or Large Language Model capabilities to improve analytical throughput and experimentation quality.
- Experience with SaaS experimentation tools such as Statsig, Eppo or GrowthBook, or with an in-house platform.

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at AccessibleRecruiting@tripadvisor.com.

If you have any additional questions about careers at Tripadvisor you can email us at recruitment@tripadvisor.com. We have all the answers!

#LI-Hybrid

## #LI-SM1

## About Tripadvisor

## Company Overview
- **One-liner**: Tripadvisor is the world's largest travel guidance platform, helping hundreds of millions of travelers each month plan, book, and share experiences using over a billion reviews and opinions.
- **Entity Type**: Public (NASDAQ: TRIP)
- **Headquarters**: Needham, Massachusetts, United States
- **Founded**: Not publicly available in provided sources (commonly known as 2000, but not cited)
- **Founders**: Not publicly available in provided sources (commonly known as Stephen Kaufer, but not cited)

## Core Business
- **Primary Industry**: Travel technology / Software development
- **Target Customers**: B2C (travelers seeking reviews, booking, and trip planning) and B2B (hotels, restaurants, attractions, and experience providers)
- **Mission Statement**: “To bring people, passions, and places together and make everyone a better traveler.” [careers.tripadvisor.com](https://careers.tripadvisor.com/)

## Products & Services
- **Tripadvisor.com / App**: The core platform offering reviews, ratings, and booking for accommodations, restaurants, and attractions.
- **Viator**: Marketplace for bookable tours, activities, and experiences.
- **TheFork**: Restaurant reservation platform (primarily in Europe).
- **Cruise Critic**: Cruise reviews and information.
- **FlipKey / Holiday Lettings**: Vacation rental listing platforms.
- **SeatGuru**: Airline seat maps and in-flight amenity information.
- **SinglePlatform**: Digital menu and local business listing management.
- **Bokun**: Booking and inventory management software for tour operators.

## Market Standing
- **Valuation / Market Cap**: $3.5 billion (as of search date) [linkedin.com](https://www.linkedin.com/company/tripadvisor)
- **Key Metric**: Annual Revenue of $1.9 billion (most recent reported) [linkedin.com](https://www.linkedin.com/company/tripadvisor)
- **Notable Investors / Partners**: Publicly traded; parent company is Liberty TripAdvisor Holdings Inc. [linkedin.com](https://www.linkedin.com/company/tripadvisor)
- **Growth Signals**: Serves 400M+ monthly users; over 1 billion reviews and contributions; operates in 43 markets and 22 languages; recent acquisition of Liberty TripAdvisor Holdings (2025) for $437M; headcount of 1,816 (‑1.7% YoY) [linkedin.com](https://www.linkedin.com/company/tripadvisor) [tripadvisor.com](https://www.tripadvisor.com/)

## Competitive Advantages
- **Massive User-Generated Content**: Over 1 billion reviews and opinions across nearly 8 million businesses create a strong network effect.
- **Global Brand Recognition**: One of the most recognized travel brands worldwide, with presence in 75 countries.
- **Diverse Product Portfolio**: From reviews to booking to restaurant reservations (TheFork) and experiences (Viator), covering the full travel journey.
- **Data Moat**: Decades of traveler behavior data enable personalization and AI-driven recommendations.

## Strategic Focus
- **Next Chapter in Travel**: CEO Matt (last name not provided) emphasizes “writing the next chapter” and supporting small businesses. [careers.tripadvisor.com](https://careers.tripadvisor.com/)
- **AI & Personalization**: Recent departures of AI leadership suggest ongoing transformation; job postings include senior engineering and product roles focused on data and AI.
- **Hybrid Work & Global Talent**: Activity-based working model encourages in-person collaboration while supporting remote flexibility across offices in the Americas, EMEA, and APAC.

## Why Work Here
- **Culture & Values**: Described as “fueled by curiosity, flexibility, and collaboration” with a shared love of travel. [careers.tripadvisor.com](https://careers.tripadvisor.com/life-at-tripadvisor)
- **Work Model**: Activity-based working (hybrid) – some roles optimized for office, others for home; all full-time employees expected to spend some in-person time.
- **Benefits**: Full medical premium coverage for employee-only plans (some options), dental, vision, Employee Assistance Program (EAP), free Calm subscription, virtual babysitting/wellness support via SitterStream. [careers.tripadvisor.com](https://careers.tripadvisor.com/life-at-tripadvisor)
- **Career Development**: Award‑winning development program focused on growing yourself, others, and the business; live and on‑demand learning experiences. [careers.tripadvisor.com](https://careers.tripadvisor.com/life-at-tripadvisor)
- **Diversity & Inclusion**: Employee Resource Groups (ERGs) for underrepresented communities; recognized as a leader in LGBTQ+ Workplace Inclusion (2026). [careers.tripadvisor.com](https://careers.tripadvisor.com/)
- **Employee Ratings**: 3.6/5.0 on LinkedIn (1,668 reviews); Work‑Life 4.2, Compensation 3.9, Culture 3.9. [linkedin.com](https://www.linkedin.com/company/tripadvisor)
- **Global Offices**: Major hubs in Needham (MA), New York, London, Oxford, Paris, Sydney, Tokyo, Singapore, and many more. [careers.tripadvisor.com](https://careers.tripadvisor.com/life-at-tripadvisor)

## Sources
1. [careers.tripadvisor.com](https://careers.tripadvisor.com/) – Official careers page, mission, benefits, culture
2. [careers.tripadvisor.com/life-at-tripadvisor](https://careers.tripadvisor.com/life-at-tripadvisor) – Life at Tripadvisor, benefits, offices, ERGs
3. [linkedin.com/company/tripadvisor](https://www.linkedin.com/company/tripadvisor) – Company overview, financials, headcount, recent departures, acquisitions
4. [tripadvisor.com](https://www.tripadvisor.com/) – Core platform, reviews count, user base

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