Senior Data Scientist, Product Analytics

At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.

The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our focus on customer-centric innovation enables us to develop products that build loyalty and repeat business. We partner closely with teams across Expedia Group to drive growth and achieve results for our customers and the company.

We're looking for a senior-level individual contributor to provide valuable analytics and decision support to drive Expedia's Localization product within Content Product Analytics.

In this role, you will partner with cross-functional teams to contribute to many aspects of product development, including understanding user behavior, A/B experimentation, and problem-solving using statistics and causal inference techniques.

• Develop and deploy advanced machine learning models to solve complex business challenges and drive data-informed decision making.
• Design and lead complex A/B and causal experiments to measure the impact of localization changes on traveler engagement and booking conversion; own the experimentation framework for the Localization product area
• Translate complex multilingual data insights into compelling narratives for product, engineering, and executive audiences; influence roadmap prioritization through data.
• Write advanced SQL and Python to build scalable, automated analytics pipelines and self-serve dashboards
• Collaborate with cross-functional teams to architect and implement end-to-end data pipelines and intelligent systems that operate at production scale.
• Lead and mentor data scientists and engineers, fostering technical excellence and a culture of continuous learning.
• Safely integrate and operate AI/ML-enabled solutions that improve outcomes, ensuring models are reliable, ethical, and scalable.
• Co‑own with Product and business leaders the metric frameworks and decision workflows for your area

• Bachelor’s degree or higher in Statistics, Economics, Computer Science, Data Science, or a related quantitative field; or equivalent related professional experience
• 8+ years of experience in data science, applied science, or analytics (6+ years with MS/PhD) in an industry setting
• You are a proven expert in statistical modeling and experiment design — including A/B testing, quasi-experiments, and causal inference methods (e.g., Pre/Post, causal impact, multivariate, multi-armed bandit)
• You have hands‑on experience building ML/NLP models at production scale (e.g., text classification, semantic similarity, quality scoring)
• You have advanced proficiency in SQL and Python, with ability to write clean, production-quality code
• You have experience working with large-scale, unstructured text data and LLMs — including prompt design, evaluation (e.g., golden sets, LLM‑as‑judge), and RAG patterns
• You have demonstrated ability to mentor junior data scientists, balance speed, risk, and analytical rigor
• You have experience with advanced visualization techniques / best practices, and building scalable dashboards
• You operate independently, managed cross‑function projects and able to influence product and business strategy through data, and storytelling skills

Please note that this role is only available in the following location:
London
, in alignment with our flexible work model which requires employees to be in‑office at least three days a week. We are unable to offer…