Machine Learning Scientist III - Package Pricing

Machine Learning Scientist III - Package Pricing Hybrid - Washington - Seattle Campus Apr 27, 2026

$138K - $193K

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 when one of us wins, we all win. Introduction to the Team As part of the Machine Learning Science organization at Expedia Group, you’ll help build a scalable, intelligent pricing system that directly shapes how we balance volume and profitability across multiple lines of business. The decisions this system drives influence billions of dollars in revenue and are visible at the highest levels of the company. In this role, you will: Design, build, and improve ML models and systems that power Expedia Group products, with a focus on measurable business and customer impact. Perform end‑to‑end model development, including problem formulation, data exploration, feature engineering, training, evaluation, and deployment in production environments. Develop robust data pipelines, data transformations, and data quality checks to ensure high‑quality input signals for ML models and experimentation. Partner with product, engineering, and analytics teams to translate business problems into ML solutions, define success metrics, and run experiments to validate impact. Safely integrate and operate AI/ML‑enabled solutions that improve outcomes, including familiarity with AI‑driven systems, tools, or workflows and applying AI/ML concepts to real‑world products. Contribute to system design (including model‑serving APIs and supporting data models), documentation, and best practices that enable reuse and scalability across multiple product domains. Minimum Qualifications: Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related technical field, or equivalent practical experience. Professional experience as a Machine Learning Scientist or in a similar applied ML role, working on end‑to‑end model development and deployment in real‑world products. Proficiency in at least one programming language commonly used for ML (such as Python) and experience working with data processing frameworks, model training libraries, and model evaluation techniques. Experience owning ML components or services in production, including monitoring model performance, maintaining data pipelines, and collaborating with engineering teams on APIs and data models. Preferred Qualifications: Advanced degree (master’s or PhD) in a quantitative discipline (e.g., Engineering, Statistics, Economics, or related fields). Experience working on pricing, revenue optimization, marketplace dynamics, or similar business problems. Experience designing and analyzing experiments (e.g., A/B testing) and working with noisy or incomplete data. Experience building ML models using user behavior, segmentation, or contextual signals. Familiarity with causal inference methods or optimization techniques (e.g., mixed‑integer programming) in applied settings. Benefits Full benefits package including travel perks, generous time‑off, parental leave, a flexible work model, and career development resources. Accommodation requests If you need assistance due to a disability or other physical or mental health conditions, please reach out to the Recruiting Accommodations Team. Apply For This Role Company Expedia Group Location Hybrid - Washington - Seattle Campus 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 Dormont Manufacturing Company