Product Data Scientist (Travel)

TL;DR

Product Data Scientist (Travel): Building measurement frameworks and experimentation systems for Viator’s travel marketplace with an accent on A/B testing, product analytics, and causal inference. Focus on designing rigorous experiments, modeling customer and supplier behavior, and translating complex analyses into product decisions.

Location: Remote role based in the United Kingdom

Company

hirify.global connects travelers with experiences, accommodations, restaurants, and other travel services through content, technology, and two-sided marketplaces.

What you will do

• Design and analyse A/B tests across Viator’s marketplace, including power calculations, guardrail metrics, and multiple-testing corrections.
• Develop causal inference analyses for non-randomized questions such as pricing, personalization, retention, and lifetime value.
• Own measurement frameworks, define product metrics, and build instrumentation, datasets, dashboards, and reporting systems.
• Conduct exploratory analyses and predictive modeling to identify customer and supplier behavior patterns.
• Partner with product managers and engineers to frame data questions and convert findings into actionable recommendations.
• Communicate rigorous, unbiased insights through clear narratives for technical and non-technical stakeholders.

Requirements

• Several years of experience in data science, analytics, or quantitative research in a data-driven organization.
• Advanced SQL skills and experience querying and manipulating large datasets.
• Proficiency with data visualization tools such as Tableau, Looker, or equivalent.
• Experience with the full A/B testing process, from test design through results interpretation.
• Some proficiency in Python for analysis, experimentation, and exploratory modeling.
• Ability to define ambiguous analytical questions and influence product or business decisions with data.

Nice to have

• Experience with propensity scoring, synthetic controls, difference-in-differences, or Bayesian methods.
• Familiarity with LLMs or NLP tooling for analytics use cases.
• Experience in travel or e-commerce and understanding of two-sided marketplace dynamics.

Culture & Benefits

• Work closely with product and engineering pods as an analytical thought partner.
• Opportunity to develop advanced analytics and experimentation expertise.
• Emphasis on rigorous, unbiased analysis and evidence-based decision-making.
• Support for continuous learning and upskilling in new tools and techniques.