Join Data Science Festival – London in partnership with Skyscanner in September for two great speakers.

Please register for a ballot ticket here: GET TICKETS

Due to the popularity of Data Science Festival events, we are now allocating event tickets via a random ballot. Registering here enters you into the ticket ballot for the Data Science Festival Event at Skyscanner on September 25th, 2018, the ballot will be drawn on the 21st September 2018. Those randomly selected will then be e-mailed tickets for the event, with the joining details.

If you get an allocated ticket, please bring a copy of your paper ticket or your ticket on your phone to the event to check in with your QR code. Tickets are non-transferable.

SCHEDULE

6:00pm Guests arrive

6:30pm РRuth Garcia & Marco Bertetti

7:15pm – Break

7:45pm – TBC

8:30pm – Networking

9:00pm – Close

Ruth Garcia – Data Scientist

Summary: Online advertising is an essential component of any business strategy. Every year, the investment on online advertising grows for mobile and web. To satisfy advertisers and increase ROI, many online ad publishers build their own ad serving platforms to manage and deliver ad inventory with flexibility and efficiently. As a consequence, the need of click prediction systems are an important aspect for the success of such systems. In this talk, I will introduce the importance of click prediction in ad manager from a publisher point of view. I will cover some of the challenges found when building click prediction models in this environment. I then explore some of the simplest algorithms used to tackle click prediction as well as some of the parameters that mostly impact performance.

Bio: Ruth is a Data Scientist at Skyscanner in London focusing on building machine learning models for online advertising. Previously, she was a researcher at the Oxford Internet Institute (University of Oxford) studying collective memory based on online information seeking patterns. She obtained her PhD at Universitat Pompeu Fabra in Barcelona and developed her thesis at Yahoo Labs Barcelona. Her work has been exposed in several international conferences on Computer Science and published in several journals and conference proceedings. In her free time, she enjoys hiking, practicing yoga, cooking and salsa dancing.

Marco Bertetti – Data Scientist

Summary: Contextual multi-armed bandits for widget optimization. Mobile applications and websites are growing more complex than ever, with new graphics, functionalities and widgets being added every day. In this ever-growing space it is important to develop new approaches to surface the right content to the right users as many time as possible. While A/B test is a widely used and solid technique, it is not always viable when the number of possible choices is very large, hundreds or thousands of tests would be required to find the best option for each situation. This talk will firstly provide an introduction to the muti-armed bandit problem. Then, a practical comparison between bandits and classic A/B testing will be shown. Closing with a practical Bandit implementation at Skyscanner.

Bio: Marco Bertetti is a Data Scientist at Skyscanner based in London, who has worked both in using reinforcement learning for mobile app content, and in shaping the structure and integrity of Skyscanner’s logging and data. Before joining Skyscanner, he has worked on different problems for a variety of companies ranging from tech startup to big retailer. He obtained a degree in Globalization, International Institutions and Economic Development at the University of Trento before moving to London. In his free time, he likes photography, cooking and rock climbing.