Machine learning scientist ii

Ph3Overview /h3 pExpedia 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. /p pWhy Join Us? /p pTo 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. /p pWe 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. /p pExpedia Technology teams partner with our Product teams to create innovative products, services, and tools to deliver high-quality experiences for travellers, 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. /p pThe Expedia Group Machine Learning Organisation helps our customers find and book the best travel for their needs, and our suppliers compete effectively and grow their business on our travel platform. Our travel platform is powered through transforming raw data into insights that both suppliers and customers can leverage. We strive to ensure everything we do has measurable business impact. We build innovative algorithms and models that make intelligent, automated decisions, both in batch and in real time. We collaborate closely with the analytics, market management, product and technology teams. /p pWithin the Machine Learning organisation, the Partner Lodging Recommendation team develops the recommender system that guides hotel partners toward the highest‑value actions, whether running a promotion, adjusting rates, or increasing visibility. Our mission is to recommend the right action at the right moment to help partners grow revenue, improve occupancy, and deliver the best value and experience for travellers. We leverage large‑scale experimentation, forecasting, causal inference, and Generative AI to surface recommendations that directly influence marketplace efficiency, partner success, and traveller satisfaction. /p h3Responsibilities /h3 ul liCreate state-of-the-art machine learning models to solve complex business problems and improve decision-making across our travel platform /li liUtilize cloud and data technologies to train and deploy models at scale /li liSupport key business initiatives through data-driven insights /li liCollaborate with analytics, market management, product, and technology teams /li liForecast demand, suggest prices and deals, provide automated conversational AI, and offer guided recommendations for hotels /li liManage multiple tasks, own deliverables end-to-end, and prioritize workload effectively /li liCommunicate findings and implications clearly to teammates and business partners /li /ul h3Minimum experience and qualifications /h3 ul liMSc or PhD in a quantitative discipline (e.g., Machine Learning, Computer Science, Statistics, Applied Mathematics/Physics); or equivalent related professional experience /li liHands-on experience applying ML techniques to real-world problems /li liProficiency in Python with strong coding practices and performance optimization /li liSolid SQL skills for data extraction, transformation, and loading /li liExperience with distributed data environments (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS) /li liAbility to frame business problems as data science challenges and prototype effective solutions /li liHigh intellectual curiosity and a passion for tackling complex technical problems /li liProficient communication skills—both verbal and visual—for sharing insights and driving impact /li /ul h3Preferred Qualifications /h3 ul liPrevious experience in a Data Scientist, Machine Learning Scientist, or similar role /li liExperience with GenAI applications (e.g. prompt engineering, RAG, AgenticAI) /li liExperience with Causal Inference methods (e.g., propensity scoring, instrumental variables) /li liExperience with Databricks /li liStrong collaboration skills to work effectively with business partners, program management, and engineering teams /li liGood understanding of the travel industry and our data landscape /li liCommitment to staying current with latest data science developments and sharing knowledge with the team /li /ul h3Accommodation requests /h3 pIf 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 the Accommodation Request. /p pWe are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others. /p pExpedia Group\'s family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: /p pEmployment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs. /p pExpedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age. /p /p #J-18808-Ljbffr