Machine Learning Scientist III

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. Why Join Us 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 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. Introduction to team 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 ML and AI 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. What You’ll Do 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. Who you are Experience & Education 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. Functional & Technical Skills 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. Able to design end‑to‑end ML solutions: framing the problem, choosing data sources, selecting algorithms, and defining evaluation strategy. Experience with the machine learning software development lifecycle, including experimentation, deployment, monitoring, and iteration in production. Strong programming skills in at least one major ML language (e.g., Python, Scala, Java) plus SQL; writes clean, modular, maintainable code. Technical Fluency: Strong programming skills in Python and its data science ecosystem (e.g., pandas, scikit‑learn, pySpark), 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. Highly Desired Experience Domain knowledge in customer service, recommendation systems, operational applications of ML, and/or e‑commerce. Experience with reinforcement learning or other advanced ML techniques is a plus. Experience building and deploying models using GenAI/LLM technologies. Experience translating research and academic papers into improved model designs and techniques. Minimum Qualifications Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience. 5+ years of relevant professional experience. Proven ability to design end‑to‑end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring. Strong programming skills in Python and its data science ecosystem (such as pandas, scikit‑learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases. Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring. Preferred Qualifications MS or PhD in a quantitative field such as Computer Science, Economics, Statistics, Physics, or a related discipline. 3+ years of hands‑on industry experience building, deploying, and iterating on machine learning models that solve real‑world problems in production environments. Proven ability to design end‑to‑end ML solutions, including problem formulation, identification and preparation of data sources, algorithm selection, feature engineering, evaluation strategy, and production deployment and monitoring. Strong programming skills in Python and its data science ecosystem (such as pandas, scikit‑learn, PySpark) and proficiency in SQL, with experience following software engineering best practices and contributing to shared codebases. Familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from experimentation through operational monitoring. Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee’s passion for travel, we offer a wellness & travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits. The total cash range for this position in Seattle is $137,500.00 to $192,500.00. Employees in this role have the potential to increase their pay up to $220,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. The total cash range for this position in San Jose is $149,000.00 to $208,500.00. Employees in this role have the potential to increase their pay up to $238,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience. Pay ranges may be modified in the future. Accommodation requests: If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through Accommodation Request. Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. This employer participates in E‑Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee’s I‑9 to confirm work authorization. #J-18808-Ljbffr