Machine Learning Scientist II

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. Machine Learning Scientists II Within the AI & Data organization, the Marketplace Science team develops, optimizes and operationalizes applied science driven marketplace levers that support a healthy, trusted marketplace. The Marketplace Health team builds systems that detect behaviors indicating trust, safety, and marketplace-health risk before they result in larger issues. This work helps protect traveler trust and supports a reliable experience across Expedia Group’s marketplace.

In this role, you will: Own machine learning projects end to end, from understanding the business need and defining the approach through execution, launch, measurement, and iteration. Develop and improve the Marketplace Health Model system to identify behaviors associated with trust, safety, and marketplace-health risks. Translate complex marketplace challenges into scalable machine learning and statistical modeling solutions. Partner closely with product, engineering, operations, trust and safety, and other stakeholders to understand needs and deliver practical solutions. Stay highly engaged with business outcomes by identifying opportunities where machine learning can create meaningful, measurable impact. Proactively evaluate opportunities based on potential return on investment, customer impact, risk reduction, and implementation feasibility. Design experiments and analyses to assess model performance, business outcomes, and marketplace-health improvements. Monitor deployed models and recommend enhancements to maintain quality, reliability, and relevance as marketplace behavior evolves. Communicate technical findings, recommendations, trade-offs, and project progress clearly to both technical and non-technical audiences. Identify gaps, resolve blockers, and advance projects independently while keeping stakeholders aligned. Experience and Qualifications: Graduate degree in a quantitative field (such as Computer Science, Statistics, Machine Learning, Operations Research, or similar) with focused coursework or research in ML, optimization, or statistical modeling Experience developing, evaluating, and applying machine learning models to complex business or product problems. Experience designing, developing, and deploying solutions using large language models (LLMs). Experience with Python, SQL, and common machine learning libraries and frameworks. Experience translating ambiguous problems into measurable objectives, analytical approaches, and actionable recommendations. Experience collaborating with cross-functional stakeholders to deliver machine learning solutions from concept through production. Proficient communication skills, with the ability to explain technical concepts and business implications clearly. Demonstrated ability to work both collaboratively and autonomously, take initiative, and maintain ownership of deliverables.

Graduate degree in Deep Learning, NLP, Transformer, LLM Experience developing agentic applications or LLM-powered agents. Experience with trust and safety, fraud detection, risk modeling, anomaly detection, behavioral modeling, or marketplace optimization. Experience working with large-scale, imperfect, or evolving datasets. Experience with