Senior Manager, Machine Learning Science - Bundled Products
Listed on 2026-07-31
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IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
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.
Introduction to the team
The Whole Trip AIteam at Expedia Group enables unforgettable travel experiences. The team’s responsibilities coversearchranking& recommendations for Brand Expedia across corelines of business including
Flights, Cars, Packages, and Activities. Additionally, we’re responsible for optimizing our interactions with travelers across this domain, including cache optimization, pricing forecasting, and next-best action modeling. Our approaches includebothtraditional MLas well asGenAI-based solutions.
We work closely with other teams in the Data & AI organization to continually improve our tools, processes, and platforms for building and deploying industry leadingAIsolutions.
As a Senior Manager, Machine Learning Science you and your team will own our Bundled Products ranking, recommendations, and intent modeling. You will work closely with stakeholders in Cars, Activities, Attach & Packages to help travelers book multi-item trips with Expedia by surfacing relevant offerings in the right places in the experience. Your team owns multiple high traffic, live models and with significant scope for further growth.
You will work with a dynamic group ofproduct managers,engineers, and scientists to achieve Expedia’s business goals.
In this role, you will:
Enable a team to develop industry-leading ranking & recommendation models for the travel industry to enable travelers to have memorable travel experiences
Lead and grow a team of machine learning scientists to deliver production-grade ML solutions that solve complex business problems and improve traveler and partner experiences across multiple product domains
Define and drive the end-to-end machine learning roadmap for your area, from problem formulation and data strategy through model design, evaluation, and productionization in close partnership with engineering and product
Set and enforce best practices for experimental design, A/B testing, and causal inference to ensure ML-driven decisions are statistically robust, interpretable, and aligned to business and customer outcomes
Partner with data engineering and software engineering teams to ensure ML models are scalable, resilient, observable, and well-integrated into services, APIs, and data pipelines in production
Mentor, coach, and develop ML scientists through technical guidance, peer review, and career development, fostering a culture of scientific rigor, continuous learning, and high impact delivery
Apply familiarity with AI-driven systems, tools, or workflows and AI/ML concepts to real world products, safely integrating and operating AI/ML-enabled solutions that improve outcomes across multiple lines of business
Minimum Qualifications:
- Bachelor’s Degree or Equivalent Level;
Technical Degree Preferred - 8+ years of relevant professional experience and 3+ years of people management experience
- Strong expertise in modern machine learning methods in ranking and recommendation with solid programming skills and collaboration experience with engineering teams on system, API, and data design
- Substantial professional experience leading end-to-end machine learning initiatives, including problem definition, data preparation, feature engineering, model development, offline evaluation, experimentation, and integration into production systems
- Proven experience managing or technically leading machine learning scientists or applied researchers, with ownership spanning multiple services,…
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