Machine Learning Scientist II - Experiences

Key Skills

A/B Testing, Apache Hive, AWS, Data science techniques, Deep Learning, Jupyter Notebook, Keras software library, Kubeflow, Machine learning techniques, MLflow, Python Programming, PyTorch, Scikit-learn, Snowflake, Spark Core, SQL, Statistics, TensorFlow

Job Description

Tripadvisor is looking for an exceptional scientist to join our dynamic and fast paced Machine Learning Team, focusing primarily on the Tripadvisor Experiences business. Our Experiences vertical provides customers with a collection of over 300K bookable products - experiences like glacier hikes in Alaska, guided walking tours in Lisbon, swimming with pigs in the Bahamas, and many, many more. The fast-growing user and product spaces pose a significant challenge for us: how to match users with experiences that are relevant to them, particularly in international markets where we hope to grow our footprint even further. As a Machine Learning Scientist working in this space, you will have the opportunity to apply your modeling and engineering skills to a number of different areas, but with a particular focus on sort and recommendations. You will have access to the newest development tools and huge data sets. You will deploy your solutions online and be able to observe the impact of your work in real time as you help the company grow.

We are looking for someone who is independent, curious, and motivated; who likes discussing ideas and will bring something new to the table. You will be working in a diverse environment where you’ll collaborate with a broad multidisciplinary team of ML scientists, analysts, software engineers, and product managers. You’ll be encouraged to take ownership of your projects and to find new opportunities and problems where machine learning could be applied to improve the business. Finally, you will also be provided the environment to grow technically and personally into a leader while contributing to the team.

About Machine Learning at Tripadvisor:

Tripadvisor is the web's leading travel information site. At Tripadvisor, the ML Team creates high impact systems that influence the travel decisions of millions of people per day. We apply cutting edge machine learning techniques to a wide variety of areas, including recommenders, online advertising, 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 Will Do:

• Participating in the design of machine learning models to solve a variety of core business problems across the Experiences business.
• Seek out new opportunities to apply data science and machine learning in the Experiences space.
• Prototype, evaluate, 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
• Participate in the determination of next steps for each project
  
  

Skills & Experience:

• PhD or Masters in Computer Science, Engineering, Statistics, or related field preferred
• For Masters candidates, 2+ years of relevant, practical experience
• Strong foundation in machine learning and statistics
• Proficiency in Python for numerical/statistical programming (our group relies heavily on Numpy/Pandas/Scikit-learn)
• Ability to interpret and write complex SQL queries
• Experience with big data technologies, such as Hive and Spark
• Experience with the deployment and maintenance of models - tools like Kubernetes, MLflow, AWS, etc.

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 AccessibleRecruiting@Tripadvisor.com and let us know the nature of your request. Please include the job requisition number in your message.