Machine Learning Scientist II - Performance Marketing at Tripadvisor

Tripadvisor is seeking a Machine Learning Scientist II to join their dynamic team and support performance marketing efforts. The successful candidate will apply their modeling skills to various problem spaces, including bidding for online advertising, customer modeling, experimental design, revenue optimization, attribution, and recommendations.

This role involves collaborating with a multidisciplinary team of data scientists, analysts, software engineers, and product managers within a diverse environment. The Machine Learning Scientist II will have the opportunity to take ownership of projects and identify new areas where machine learning can enhance the business.

The position can be based in the office, hybrid, or remote within Portugal.

What This Role Involves:

• Using machine learning models to solve core business problems across performance marketing.
• Seeking out new opportunities to apply data science and machine learning in the performance marketing space across all channels (e.g., Web, email, paid marketing).
• Automating ETL pipelines.
• Prototyping, evaluating, deploying, and maintaining new models in production.
• Designing AB tests and analyzing their results.
• Discovering new ways to analyze and interpret the data.
• Communicating progress and interpretation of experimental results to technical and business stakeholders.

Requirements:

• PhD or Masters in Computer Science, Engineering, Statistics, or related field preferred (or masters with 2+ years of practical experience).
• Knowledge of AB test design and analysis.
• Strong background in machine learning and statistics.
• Solid foundation on data structures and algorithms.
• Proficiency in Python for numerical/statistical programming (Numpy/Pandas/Scikit-learn).
• Ability to interpret and write complex SQL queries.
• Experience with big data technologies, such as Hive and Spark.
• Track record of leading the deployment and maintenance of models.

What This Role Offers:

• Access to the newest development tools and huge data sets.
• The opportunity to deploy solutions online and observe the impact of their work in real time.
• A diverse environment with collaboration across multidisciplinary teams.
• A culture of personal development, including social activities, journal clubs, memberships in online learning resources, and participation in industry conferences.