Machine Learning Scientist III - VRBO Pricing

Expedia•Austin, TX

1d•$137,500 - $220,000•Onsite

About The Position

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. Travel is a force for good. At Expedia Group (Expedia, Hotels.com, Vrbo, Travelocity, Orbitz, Wotif and others), it’s our mission to power global travel for everyone, everywhere, because we know that travel strengthens connections, broadens horizons, and bridges divides. Powered by more than 70+ terabytes of data and 20+ years of tech innovation, Expedia Group is one of the world’s largest travel platforms. With unrivaled knowledge of the industry and advanced tech innovation, we built a marketplace that allows us to filter through millions of different possibilities, for travelers and partners worldwide. Travel platform pricing and monetization has critical impacts on the 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 III, you will 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, operations research and optimization, ML-based demand estimation, experiment design with spillovers. And this is an applied research role – your models will be deployed to our production systems, and your results will be measured objectively through AB testing.

Requirements

3+ years industry experience and an advanced degree (PhD preferred) in a quantitative field, such as Statistics, Operations Research, Economics, Computer Science, or equivalent quantitative fields.
Expert in one or multiple areas of machine learning, causal inference, and operations research.
Comfortable to analyze complicated data sets to generate insights to guide effective solution development.
Passion for solving exciting and meaningful real-world problems using principled techniques and practices.
Focus on problem solving with pragmatical methods.
Understanding of modern machine learning and data science techniques and their mathematical underpinning.
Ability to communicate clearly and effectively to cross functional partners of varying technical levels.
Collaborates well in a team and sensitive to clients' needs, while developing warm relationships and building trust with stakeholders
Proficiency in one of the tools such as Python, Scala, etc
Proficiency with big data ecosystem (Hadoop/Spark)

Nice To Haves

Experience in pricing is a plus.
Experience with large scale marketplace experiment design and analysis is a plus.

Responsibilities

Apply solid scientific skills, strong analytical and innovative thinking to quickly learn new domains and turn innovative ideas into working solutions
Articulate technical solutions and plans to stakeholders based on detailed understanding of business requirements.
Research and implement scalable machine learning and data science solutions end to end with engineering rigor.
Follow the latest technology and research and be able to customize them to our problem space.
Design success metrics for both short-term and long-term performance.
Guide solutions using data insights based on deep understanding of business domains.
Collaborate with other machine learning and data science teams to build a great data science culture in Expedia Group.