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Tripadvisor Logo

Machine Learning Scientist II (Fraud)

Id Job: 3172774

🏠 On-site
💼 Tripadvisor
📍 Remote
Today
💰

Job Description

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to
bring your unique identities, abilities, and experiences, so we can collectively revolutionize travel and together find the good out there.

At Tripadvisor, we never stop learning. This is true both individually and as a company, where constant experimentation helps us to understand how we can continue to grow and improve the
user experience for our 500 million unique monthly visitors worldwide. Data-driven decision making is at the core of what we do.

About Data Science at Tripadvisor

Tripadvisor is the web's leading travel information site. At Tripadvisor, the Data Science Team creates systems that influence the travel decisions of millions of people per day. It applies
cutting edge machine learning techniques to a wide variety of areas such as recommenders, vision, and text processing - especially with a focus on natural language processing (NLP). To
ensure continued success, Tripadvisor promotes a culture of personal development, including social activities, journal clubs, memberships in online learning resources, and participation in
industry conferences. Have a great time while shaping the future of travel!

About the Role

The Tripadvisor Data Science Team is looking for an exceptional individual to help design and build next generation systems that models the fairness, reliability and validity of Tripadvisor
audiences and content. Such a model will allow significant improvements in our ability to offer to travelers the broadest, most relevant travel products. This individual will also have the
opportunity to work on other projects on the team, including those related to text and image processing.

What You Will Be Doing

problems
Qualifications

What you'll get

Highly competitive salary along with the following:
We strive to create an accessible and inclusive experience for all candidates.


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