Booking.com Data Science
The Data Science and Machine learning blog of Booking.com
Dima Goldenberg
Machine Learning @ Booking.com
Sonya Liberman
Leading applied Machine Learning teams. Especially enjoy bringing theory to production and bridging the gap between business needs and technological solutions.
Maud Schwoerer
Data Scientist at Booking.com
Felipe Moraes
Machine Learning Scientist at Booking.com. PhD in Information Retrieval at TU Delft. Ex-Amazon Alexa.
Latest Posts
Booking.com’s publications at the 18th ACM conference on Recommender Systems
Booking.com’s mission is to make it easier for everyone to experience the world. We invest in technology that helps take the friction out…
Predicting cancellations with survival modeling
Within Booking.com, we have a long tradition of predicting reservation cancellation probability using machine learning models. Historically…
A recap of the Experimentation Conference 2024 at Booking.com
By Melanie Mueller and Jorden Lentze
Meta-experiments: Improving experimentation through experimentation
At Booking.com, we are proud of our data-driven culture. A hallmark of this is our extensive use of A/B testing everywhere in the company…
Raising the bar by lowering the bound
Why tackling overestimation is essential for product development
How good are your ML best practices?
by George Chouliaras, Kornel Kielczewski, Amit Beka, David Konopnicki and Lucas Bernardi
Booking.com @ KDD 2023
Booking.com contributions at the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining at Long Beach, CA, USA
Sequential Testing at Booking.com
Reliable and fast product decisions
Booking.com @ RecSys 2022
Booking.com’s publications at the 16th ACM conference on Recommender Systems
How to stop wasting time fixing broken machine learning pipelines
Let me set the scene: it’s Monday morning, and you just came back from a relaxing weekend. You turn on your laptop, excited to get back to…
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