Expedia Product & Technology builds innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A singular technology platform powered by data and machine learning provides secure, differentiated, and personalized experiences for the traveler and our partners that drive loyalty and customer satisfaction.

Personalization is one of three core AI capabilities at Expedia Group, alongside Agentic Experiences and Context Engineering. Our mission is to build an integrated, scalable personalization capability that powers traveler discovery, shopping, and servicing experiences across onsite and offsite journeys. This includes a shared, enterprise-wide personalization platform spanning unified traveler identity and profile, AI-driven traveler profiles and segmentation, real-time decision services, and governed data contracts to enable safe, reliable, low-latency personalization at scale.

As a Distinguished Scientist, you will set the scientific direction for personalization across Expedia Group—partnering closely with product, engineering, and platform leaders to ensure personalization measurably improves customer outcomes and business performance (e.g., CVR, LTV, repeat bookings) while remaining privacy-forward and operationally excellent.

In the role you will

• Shape the long-term vision and scientific agenda for Personalization across Expedia Group, spanning traveler discovery, shopping, marketing, and servicing experiences.

• Serve as a strategic thought partner to senior product, engineering, and platform leaders—translating business goals into clear technical roadmaps and investment priorities, with a strong bias toward iterative, test-and-learn delivery.

• Define the decisioning and modeling strategy across key personalization domains (e.g., recommendations, ranking, search personalization, audience/targeting), ensuring shared capability reuse and avoiding siloed solutions.

• Lead applied research and innovation in areas such as recommender systems, sequential and session-based modeling, foundation models for personalization, explore/exploit (bandits), counterfactual evaluation/causal methods, and multi-objective optimization aligned to long-term value.

• Be hands-on building prototypes and components, designing and running offline/online experiments, and working with engineering teams on end-to-end systems from concept to production.

• Define and champion a rigorous multi-metric success framework and ensure the organization measures what matters. Partner with data and experimentation platforms to elevate data quality, instrumentation, and observability—ensuring high-fidelity behavioral and conversion data and accelerating experimentation velocity through segment-aware testing and CLV-based decisioning.

• Represent Expedia Group as a recognized internal and external authority in personalization and applied ML (e.g., impactful publications, patents, major conference talks, open-source contributions).

Minimum Qualifications

• MS in Computer Science, Machine Learning, or related field, or equivalent professional experience, with 15+ years of experience in applied ML/AI roles at scale.

• Deep expertise in large-scale personalization, recommendation systems, and ranking—covering problem formulation, feature/model development, offline evaluation, and online experimentation. Knowledge of recent approaches to personalization such as e.g. Semantic IDs, Transformer-based models and embeddings, and personalization for context engineering.

• Demonstrated ability to deliver large, complex ML/AI projects from concept to production, including reliable operation of business-critical, externally facing services.

• Strong experience with experimentation and measurement, including segment-aware testing and long-term value (CLV/LTV) frameworks.

• Proficiency in one major ML programming language (e.g., Python) and familiarity with data pipelines and model deployment tooling and practices.

• Demonstrated ability to define best practices at a department or organizational level and to drive improvements to business processes, knowledge, and technical maturity through workshops, coaching, and thought leadership.

• Exceptional communication and storytelling skills, including presenting to large audiences and executive stakeholders and communicating complex technical concepts to non-technical audiences with clear visual aids and narratives.

Preferred Qualifications

• Proven track record as a recognized industry leader in personalization and applied ML (e.g., impactful publications, patents, open-source contributions, major conference talks).

• An entrepreneurial mindset, with a history of converting proofs-of-concept into high-impact, productionized solutions with measurable business outcomes.

• PhD in Computer Science, Machine Learning, or related field.

• Broad and deep understanding of machine learning theory and practice, including advanced statistical methods and complex model design across multiple ML subdomains; comfortable operating across modeling, data, and systems.

• Experience designing real-time/streaming personalization decision services and optimizing cost-to-serve and performance at scale.

• Strong grounding in privacy-forward data and AI practices and governed data contracts for compliant personalization. ·

• Experience working in e-commerce or two-sided marketplaces, with a strong understanding of how personalization integrates with search, recommendations, advertising, pricing, and servicing.