Location
London

Hours
Full Time

Salary
Negotiable

About the Role
The Tripadvisor Group connects people to experiences worth sharing and aims to be the world’s most trusted source for travel and experiences. Leveraging our brands, technology, and capabilities, we connect a global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. Our subsidiaries include Tripadvisor, Viator, and TheFork.

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

As a Senior Data Scientist on our experimentation team, you will partner with Product and Engineering teams across various product areas to guide how investigations are set up, determine whether changes worked, and understand why. Your impact will come from improving experimentation processes—metrics, guidance, tooling, and protocols—that enable teams to move quickly without sacrificing rigour.

You will lead measurement challenges that standard A/B tests cannot address, such as limited traffic, user competition for supply, or long-term outcome evaluation. Your responsibilities include owning the experimentation and measurement strategy for your domain, providing guidance and tooling to improve experimentation velocity, designing complex experiments, and going beyond whether a change worked to why it worked and its generalizability across users, markets, and time.

You will assess how decisions affect platform health and growth, define and operationalise metric frameworks including guardrails and proxies, improve measurement sensitivity, standardise recurring analytical processes using automation and AI, influence roadmap prioritisation through evidence, and raise technical quality by mentoring and reviewing experiment designs and analyses.

Experience
- Extensive experience in data science or a similar quantitative role with a proven track record of supporting and influencing product organisations.
- Authoritative command of experimentation including experimental design, variance reduction, causal inference, bandits, and Bayesian methods.
- Expert proficiency in Python and SQL.
- Deep hands-on experience with statistical modelling, (quasi) experimentation, multi-arm bandits, and machine learning techniques such as regression, classification, and clustering.
- Demonstrated ability to define, implement, and operationalise product and feature-level metrics from scratch.
- Proven ability to improve other teams’ experimentation speed and quality through guidance, tooling, and protocols.
- Ability to critically assess product decisions’ impact on platform health and growth.
- Experience standardising processes and frameworks across multiple teams, including AI and automation.
- Strong cross-functional partnership skills across Product, Engineering, Data Platform, and other functions.
- Leader in critical thinking with a habit of verifying result trustworthiness before interpretation.
- Exceptional communication skills to explain measurement, methods, and uncertainty to technical and non-technical audiences.

About you
- You thrive in a collaborative environment and enjoy mentoring others.
- You are passionate about rigorous experimentation and data-driven decision making.
- You have a strategic mindset with the ability to influence roadmaps and prioritisation.
- You are comfortable working in complex, high-scale marketplaces or platforms with long purchase cycles and seasonality.
- You embrace innovation, including applying AI and Large Language Model capabilities to improve analytical throughput and experimentation quality.

Qualifications
Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

Preferred Experience
- Experimentation in marketplaces with interference between users and shared supply.
- Advanced variance reduction techniques beyond single pre-period covariates.
- Building or validating proxy metrics for long-horizon outcomes.
- Exposure to Bayesian approaches for low-traffic surfaces or pooling evidence across small markets.
- Experience with SaaS experimentation tools such as Statsig, Eppo, GrowthBook, or in-house platforms.
- Experience improving experimentation practices at team or organisational level through frameworks, tooling, or enablement.
- Experience in high-scale marketplaces, e-commerce, or travel platforms.