17-18 Campus - Machine Learning Engineer
TripAdvisor, Needham, MA
Know better. Book better. Go better.
TripAdvisor is the largest travel site in the world. We get millions of unique visitors on a monthly basis.
Do you want to apply your machine learning expertise to find solutions for the largest travel site on the web? Do you get excited about the prospect of working with not just big data, but huge data? Would you like to work across diverse areas including personalization, fraud detection, and natural language processing?
TripAdvisor’s Machine Learning team to works on machine learning and statistical analysis problems across several groups in the company. As a member of this group you’ll use these techniques to implement new solutions and improve existing approaches to large scale data analysis. You’ll be relied upon to research, design, and implement your projects. You must be comfortable communicating your approach to project managers across the company.
- Working with Hadoop, Redshift, and other big data systems
- Applying machine learning techniques to personalize the site experience for our users
- Building algorithms to help our review fraud team catch bad guys
- Working on various classification and regression problems over our huge database of traveller reviews and site data
- Bachelors or Master’s Degree in Computer Science, Computer Engineering, Math or a related field. Advanced degree preferred.
- A passion for solving real world problems with machine learning
- Experience working with collaborative filtering, clustering, classification, regression, and/or statistical modeling.
- Knowledge of Hadoop, Hive, Redshift or other big data tools
- Knowledge and experience of SQL and relational databases
- Fluency with statistical tools such as R or Python scikit-learn
- Proficiency in Java or C++
- Strong computer science fundamentals (data structures and complexity)
TripAdvisor is an Equal Opportunity Employer
TripAdvisor® is the world's largest travel site*, enabling travelers to unleash the potential of every trip. TripAdvisor offers advice from millions of travelers, with 500 million reviews and opinions covering 7 million accommodations, restaurants and attractions, and a wide variety of travel choices and planning features — checking more than 200 websites to help travelers find and book today's lowest hotel prices. TripAdvisor branded sites make up the largest travel community in the world, reaching 390 million average unique monthly visitors** in 49 markets worldwide. TripAdvisor: Know better. Book better. Go better.
Want to learn more about TripAdvisor? Visit http://www.tripadvisor.com
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