Machine Learning Scientist III – Customer Service

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and we know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time‑off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

Seattle, San Jose

Are you passionate about using machine learning to improve Customer Experience? Would you like to work in the fast‑paced, competitive, customer‑focused, and data‑rich world of online travel?

Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data scientists interested in breaking new ground to tackle some of the most complex customer experience problems in the travel domain. The focus of your job will be on developing state‑of‑the‑art machine learning algorithms to power and enhance the customer experience across highly complex post‑booking recommendations, customer service, and trip management use cases.

You will tackle substantial technical challenges, from inference problems arising from long‑tail traveler data to multi‑objective optimization problems in the highly dynamic, operationally complex environment of customer service. Your passion for the craft of statistics, machine learning, and causal inference will unlock tangible growth for our business by exploiting these rich data sets and building effective solutions for travelers and our partners.

This is your opportunity to build the core algorithms that help Expedia Group's Post Booking organization bring context and intelligence to every step of the traveler journey and redefine what service excellence in travel can be. We are looking for a hands‑on scientist who is passionate about applying machine learning to complex prediction and optimization problems that drive an ecosystem that anticipates traveler needs, personalizes dynamic add‑ons and upsells, and improves service experiences, making travel more seamless for millions of customers and partners worldwide.

• Design & Implement ML Solutions:
  Take ownership of the end‑to‑end ML lifecycle for your projects, from ideation and research to deployment and monitoring.

• Test, Learn, and Iterate:
  Design and analyze tests to validate your models and quantify their business impact and design future iterations.

• Collaborate and Communicate:
  Partner closely with product managers, engineers, and business stakeholders to understand requirements, define problems, and communicate your findings and results effectively.

• PhD or MS in a quantitative field (e.g., Computer Science, Economics, Statistics, Physics).

• 3+ years of hands‑on industry experience building and deploying machine learning models to solve real‑world problems.

• Expertise in applied ML:
  Deep, practical knowledge of machine learning theory (supervised/unsupervised learning, deep learning) and statistical modeling and a strong command of experimental design (A/B testing) and causal inference to accurately measure impact.

• Technical Fluency:
  Strong programming skills in Python and its data science ecosystem (e.g., pandas, scikit‑learn, py Spark), plus proficiency in SQL. Follow software engineering best practices and contribute to the team's shared codebase.

• First‑Principles Problem Solver:
  Skilled at dissecting ambiguous problems and clearly communicating complex technical ideas.

• Domain knowledge in customer service, recommendation systems, operational applications of ML, and/or e‑commerce

• Experience building and deploying models using GenAI/LLM technologies