Manager, Applied Research
Are you passionate about using Machine-Learning to improve Customer Experience? Would you like to work in the fast-paced, competitive, customer-focused, and data-rich world of online travel?
Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data scientists interested in breaking new grounds to tackle some of the most complex computational problems in the marketing domain. The focus of your job will be on developing state of the art machine learning algorithms to power various aspects of highly complex global marketing campaigns. We spend hundreds of millions of dollars participating in highly dynamic auctions in travel Metasearch sites (TripAdvisor, Kayak, Trivago) and Paid Search (Google, Bing, Yahoo). These marketing channels would benefit from solving a range of fundamental problems with varying levels of complexity, e.g., from inference problems that arise due to sparse data to solving complex optimization problems impacted by dynamic market and user behavior. We have large, rich, and untapped data sets that can be collected only by spending huge amounts of money. Your passion for the craft of statistics, optimization, and machine-learning will help unlock tangible growth for our business by exploiting these data sets.
What you’ll do:
Manage a small team of scientists working on high impact problems
Provide technical leadership, identify key business challenges and opportunities, and develop end-to-end software solutions using machine learning and optimization methods
Model rich and complex online travel data to understand, predict and optimize key performance indicators
Document technical details of your work
Collaborate with business partners, and engineering team to ensure that solutions meet business needs, permit valid inferences and have functional feasibility
Who you are:
PhD or MS in Computer Science, Statistics, or related technical field with a background in both machine learning and software development; or Equivalent related professional experience
5+ years of experience applying Machine Learning in an industry setting
Mentoring Experience mentoring junior scientists
Excellent grasp of statistical concepts and methods
Fluent in Python/R and PySpark
Solid understanding and experience in database technologies, including SQL and NoSQL
Strong communication skills both written and oral
Hands-on experience with deep-learning technologies are a plus
Experience with distributed version control i.e. git or mercurial
Knowledge of A/B test design, implementation and evaluation
Experience and application of optimization techniques such as linear programming or meta-heuristics
Experience with data visualization tools and packages.
About Expedia Group
Expedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, Egencia®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™.
© 2021 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50Expedia 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.
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