Data Scientist III, Marketplace and Partner Product Economics

Key Skills

Java Programming, Python Programming, Scala Programming, SQL

Job Description

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Data Scientist III, Marketplace and Partner Product Economics

At Expedia Group (EG), our mission is to power global travel for everyone, everywhere. To succeed in that mission, we are developing new tools to help us build the best experiences for our travelers. Do you want to be on the forefront of enabling EG to make durable, data-driven decisions? Then we have a job for you.

The Expedia Group Product Analytics team is searching for a Data Scientist III to join a newly formed team. You will be on the forefront of building the scientific products and processes to measure and drive the long-term flywheel for the Expedia marketplace, which includes all aspects of Expedia’s business, from search ads to the products that help our partners manage their inventory on Expedia.

You will develop and implement the methods to scientifically measure, predict, and forecast long-term value lift for Expedia customers, and the systems to report results. You will partner cross-functionally with leaders across the company to ensure EG leverages the right tools and data to make decisions that impact all our travelers. This is a new, critical role whose expertise will have broad impact on business priorities across EG.

The ideal candidate will have experience executing on ambiguous problems through methodical inquiry, and will have a track-record of delivering substantial impact.

This role can be located in Seattle, Austin, or Chicago.

What you’ll do:

• Solve a broad range of problems by applying theoretical and advanced statistical methods
• Evaluate and assess the usage of advanced methods such as Stochastic Processes, Bayesian Neural Networks, Markov Models, Discriminant and Factor Analysis, and applies them while considering underlying assumptions and limitations
• Incorporate the latest academic and published research including neural network, transformers and reinforcement learning domains
• Select valid approaches, appropriate in terms of level of effort, favoring iterative delivery that solve for the objective, not the ask (i.e. not just order-taking)
• Use advanced and sophisticated understanding of the business problem space to inform the design of the solution
• Proactively contribute to cross team collaboration and lead alignment of work with broader initiatives tailoring messaging to audience and filters relevant communication
• Collaborate with peers within and across teams, bearing team and company goals in mind
• Contribute to development of a strategic roadmap to deliver scientific solutions on long-term value prediction and related areas
• Collaborate individual contributors and managers and drive the development of a diverse and high-quality talent pipeline
• Engage with the research community and apply concepts to make recommendations to current projects
• Write code that is clean, maintainable, optimized, modular with good naming conventions using software design principles, data structures and/or design patterns and computer science fundamentals to
• Design and implement new model performance measurement and evaluation artifacts/techniques to suit customized machine learning solutions
• Act as a technical mentor for your peers
• Frame challenging business problems as a data science problem and set of concrete set of tasks
• Leverage others’ skills, knowledge and expertise effectively in problem solving and delivering impact

Who you are:

• Bachelor's degree in Economics, Statistics, Computer Science or any other related field; or equivalent related professional experience
• Deep theoretical foundation, applies advanced statistical methods to a broad range of problems
• Worked in at least in one long term projects that span several quarters may include academic work
• Experience building and maintaining science projects/products in production environments
• Active participant in technical community, such as blog posts, tech talks, open source contributions or data mining competitions
• Demonstrate significant expertise in at least one major ML programming language (Python, Scala…) and familiar with others
• Demonstrate in-depth understanding of econometrics and statistics, including causal inference, predictive modeling, forecasting
• Familiarity with supervised and unsupervised machine learning methods and related theory
• Have experience with advanced methods such as Stochastic Processes, Bayesian Neural Networks, Markov Models, Discriminant and Factor Analysis; and applies them while considering underlying assumptions and limitations