Machine Learning Scientist II
Listed on 2026-08-07
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IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, Data Analyst
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.
Our Expedia Product & Technology division builds innovative products, services, and tools to deliver high-quality experiences for travelers, partners, and our employees. A unified, 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.
The Machine Learning Scientist II role sits on the Lodging Search Ranking AI team inthe Expedia Product & Technology division of Expedia Group.
At the heart of the 3-side marketplace (the traveler, the property owners and the platform), this team develops and optimizes ranking modules with state-of-the-art machine learning/ genAI techniques to power lodging search and personalized lodging ranking/recommendations for the multiple brands and lines of business in our portfolio.
In this role, your expertise and passion for innovation, developing cutting-edge technology and implementing industry-leading solutions, will improve the experience of millions of travelers and travel partners each year. This is an applied scientist role: your models will be deployed to our production systems, and your results will be measured objectively via A/B testing, directly impacting our business results. We collaborate closely with the analytics, product, and engineering teams.
Inthis role, you will:
Develop, implement, and optimize machine learning models that power data-driven features and products, from problem framing through production deployment and iteration.
Design and evaluate experiments, offline evaluations, and A/B tests to measure model impact, using statistical rigor to compare alternatives and drive decisions.
Collaborate with engineers, product managers, and analysts to translate ambiguous business problems into well-scoped ML solutions, including data requirements, modeling approach, and success metrics.
Apply strong data modeling, feature engineering, and model selection skills across multiple domains, ensuring models are robust, explainable, and performant at scale.
Safely integrate and operate AI/ML-enabled solutions that improve outcomes, including monitoring model performance, detecting degradation, and driving continuous improvements in production.
Demonstrate familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real-world products, contributing reusable methodologies and best practices that can be leveraged across teams and problem spaces.
Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience.
2+ years of relevant professional experience.
Proven ability to own ML solutions for a well-defined service or product area, including data exploration, model development, offline and online evaluation, and partnering with engineering for integration.
Proficiency in at least one major programming language used for ML (such as Python) and common ML/AI frameworks and tooling for model development, training, and evaluation.
Solid grounding in core ML concepts (e.g., supervised and unsupervised learning, model generalization, overfitting, evaluation metrics), and experience working with real-world, noisy datasets.
Advanced degree (Master’s or PhD) in a quantitative field with a focus on machine learning, statistics, or AI, with experience applying research ideas to…
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