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.