Machine Learning Scientist II – VRBO Pricing

Machine Learning Scientist II – VRBO Pricing

Introduction to the team:

Travel platform pricing and monetization has critical impacts on business health. The Machine Learning Science team is building a scalable and robust system to enable pricing as a lever to optimize business performance. The system should be steered based on desired outputs, such as a given tradeoff between volume and profit. Our work directly decides prices across different lines of business, influencing multi-billion dollar revenue.

As a Machine Learning Scientist II, you will help to research and build this pricing system. You will work on end-to-end pricing problems. You will collaborate with a strong team of machine learning scientists, data scientists, engineers, product managers, and operation analytics. You will contribute to an area of active scientific research: causal inference using machine learning methods, mixed integer programming, ML-based demand estimation, experiment design with spillovers.

In this Role, you will:

• Help to research and implement scalable machine learning and data science solutions end to end with engineering rigor.
• Articulate technical solutions and plans to stakeholders.
• Follow the latest technology and research and be able to customize them to our problem space.
• Guide to solutions using data insights.
• Collaborate with other machine learning and data science teams to build a great data science culture in Expedia Group

Minimum Qualifications:

• Advanced degree in a quantitative field (Computer Science, Statistics, Operations Research, Economics) or equivalent professional experience.
• Hands-on experience in machine learning, operations research, or causal inference.
• Strong analytical skills for working with complex datasets and generating actionable insights.
• Proficiency in Python or Scala.
• Familiarity with big data ecosystems such as Hadoop or Spark.
• Solid understanding of modern ML and data science techniques and their mathematical foundations.
• Ability to communicate clearly and effectively.
• Pragmatic approach to problem-solving.

Preferred Qualifications:

• Experience in pricing strategies or revenue optimization.
• Background in large-scale marketplace experiment design and analysis.
• Exposure to mixed-integer programming and ML-based demand estimation.
• Knowledge of causal inference methods applied to real-world business problems.
• Experience collaborating in cross-functional teams with engineers, product managers, and analytics professionals.