Job Description

Expedia Technology teams partner with our Product teams to create 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 that drive loyalty and traveler satisfaction.

Introduction to the Team:

The Traveler Engagement & Loyalty team at Expedia is at the forefront of innovation in AI-driven recommendation systems. We're dedicated to enhancing customer experiences, increasing engagement, and strengthening traveler relationships through cutting-edge machine learning solutions. Our work directly impacts millions of travelers worldwide, shaping their journey from dreaming to booking and beyond.

Join a newly formed Machine Learning Science team at Expedia Group focused on transforming Customer Relationship Management (CRM) through intelligent, personalized outbound communications. From crafting tailored travel recommendations to optimizing engagement strategies, your work will directly influence millions of travelers globally. This is a rare opportunity to build foundational systems in a high-impact domain, backed by Expedia’s AI-first vision.

In this role, you will:

• Build and optimize recommendation models for CRM use cases, including personalized email campaigns and retention strategies.
• Apply deep learning and causal inference to sparse, noisy, and dynamic customer interaction data.
• Design and analyze A/B experiments to validate model performance and drive product decisions.
• Collaborate with ML Engineers to deploy models at scale, ensuring robustness and reliability in production environments.
• Translate business objectives into measurable machine learning goals aligned with customer engagement outcomes.
• Stay current with advancements in recommendation research, deep learning architectures, and personalization systems.

Minimum Qualifications:

• MS, or BS in Computer Science, Machine Learning, Statistics, Engineering, or a related field; or equivalent professional experience
• 3+ years of experience building production-grade recommendation or personalization systems.
• Strong understanding of collaborative filtering, deep learning for recommendations, reinforcement learning, and causal inference.
• Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
• Experience with distributed systems like Apache Spark.
• Familiarity with A/B testing and experimentation methodologies.
• Ability to work with large-scale, real-world data with attention to bias, fairness, and privacy.
• Excellent communication skills for both technical and non-technical audiences.

Preferred Qualifications:

• PhD in Computer Science, Machine Learning, Statistics, Engineering, or a related field
• Experience in the travel or e-commerce industry.
• Familiarity with cloud platforms (AWS, GCP, Azure).
• Publications in top-tier ML conferences or journals.
• Contributions to open-source ML projects.
• Experience in personalization systems or CRM-focused ML applications.
• Experience taking models from prototype to production in collaboration with Machine Learning Engineering teams.

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