Product Data Scientist (Travel)

TL;DR

Product Data Scientist (Travel): Building and optimizing measurement frameworks and experimentation processes for the Viator marketplace with an accent on A/B testing and causal inference. Focus on designing rigorous experiments, surfacing actionable insights from large datasets, and influencing product decisions through advanced analytics.

Location: Hybrid (London, United Kingdom)

Company

The hirify.global Group connects people to experiences worth sharing through a portfolio of travel brands including hirify.global, Viator, and TheFork.

What you will do

• Design and analyze A/B tests across the marketplace using sound statistical methods and power calculations.
• Implement advanced causal inference techniques such as difference-in-differences and propensity scoring to measure non-randomized impacts.
• Define key metrics and build instrumentation and reporting frameworks to track product performance.
• Perform deep-dive exploratory analyses using regression or tree-based modeling to identify LTV signals.
• Collaborate with product managers and engineers to translate data into clear, actionable product recommendations.

Requirements

• Professional experience in data science, analytics, or quantitative research within a data-driven organization.
• Advanced SQL skills for querying and manipulating large datasets.
• Proficiency in data visualization tools such as Tableau or Looker.
• Experience managing the full A/B testing lifecycle from design to interpretation.
• Proficiency in Python for data analysis and exploratory modeling.
• Must be based in London, United Kingdom

Nice to have

• Knowledge of Bayesian approaches and advanced statistical methods.
• Familiarity with LLMs or NLP tools for content classification and dataset enrichment.
• Experience in travel or e-commerce, specifically two-sided marketplaces.

Culture & Benefits

• Culture of rigorous, unbiased analysis and data-driven decision making.
• Emphasis on a growth mindset and continuous upskilling in advanced analytics.
• Collaborative environment working within integrated product pods.