Machine Learning Scientist II

Machine Learning Scientist II Remote

Tripadvisor
Full Time Remote 10.56 - 12.04 GBP 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.

About the Role

The Tripadvisor Data Science Team is looking for an exceptional experienced individual to help lead the design and building next generation systems to understand our travelers and products to improve customer experience. Such work will allow a significant improvement in our ability to offer to travelers the broadest, most relevant travel products (e.g., tell me the most family-friendly summertime activities in Paris). This individual will have the opportunity to lead projects on the team, including those related to recommendations, text processing, and image processing.

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, including recommenders, vision, text processing, and natural language processing. 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!

What You'll Do

  • Experience with Personalization, recommender systems, collaborative filtering, embeddings, and user lifetime value
  • Seek out new opportunities to apply data science and machine learning to the business (e.g., personalized recommendations, performance marketing, customer modeling) across all channels (e.g., Web, email, paid marketing)
  • Has experience working with other teams in solving problems and identifying opportunities
  • Lead the design of machine learning models to solve a variety of core business problems in customer acquisition, retention, and reactivation
  • Automate ETL pipelines
  • Prototype, evaluate, optimize deploy, and maintain new models in production
  • Design AB tests and analyze their results
  • Discover new ways to analyze and interpret the data
  • Communicate progress and interpretation of experimental results to technical and business stakeholders
  • Lead the determination of next steps for each project
  • Adopt cutting edge technologies to internal problems
  • Create and champion new opportunities that can affect the entire organization.
Skills & Experience

  • PhD or Masters in Computer Science, Engineering, Statistics, or related field preferred
  • Knowledge of AB test design and analysis
  • Strong background in machine learning and statistics
  • Strong foundation on data structures and algorithms
  • Proficiency in Python for numerical/statistical programming (our group relies heavily on Numpy/Pandas/Scikit-learn)
  • Ability to write complex SQL queries
  • Experience with big data technologies, such as Hive and Spark
  • Track record of leading the deployment and maintenance of models
  • 3+ years of relevant, practical experience
  • Team player
  • Loves to learn
  • Great communication skills with both technical and non-technical partners
  • Gets things done on time and on specification
  • Can work independently
If you need a reasonable accommodation or support during the application or the recruiting process due to a medical condition or disability, please reach out to your individual recruiter or send an email to [email protected] and let us know the nature of your request. Please include the job requisition number in your message.

\#LI-SM1

\#LI-Hybrid

Machine Learning Scientist II
Tripadvisor

www.tripadvisor.com
Needham, United States
Matt Goldberg
$2 to $5 billion (USD)
1001 to 5000 Employees
Company - Public
Internet & Web Services
2000
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