El 25 de mayo se ha celebrado un seminario de la Cátedra de Ciencia de Datos y Aprendizaje Automático UAM-IIC, en el que la charla fue ofrecida por Daniel Villatoro, Chief Data Scientist en Openbank con el sugerente título de “How to do evil with Data”, o “Cómo hacer el mal con los datos”.
Daniel Villatoro holds a PhD in Artificial Intelligence from the IIIA-CSIC (twice awarded, by the IFAAMAS and the UAB), and he is passionate about data, and how its profound analysis can helps us understand better the reality. His research tools of choice are urban analytics, behavioural economics, and network theory while using tools from the big data ecosystem.
Daniel is an active member of the community, publishing research articles in scientific journals, as well as maintaining a closer contact with other data enthusiast in Databeers (a data-science dissemination event cofounded by him with presence in 17 cities in 6 different countries). In his professional experience he has worked at BBVA Data & Analytics, Vodafone and currently he is Chief Data Scientist at Openbank.
The plethora of datasets available to Data Scientist inside any big corporation transfers us a great power that might convey important consequences. In numerous situations these datasets represent companies´ clients and their activities with them. In this talk we will analyze the best practices to do “evil with data”, by which we mean actions such as to promote clients churn, reduce products benefits or provide the worst client service, to mention just a few examples that can be achieved through data analysis. We will review the most modern modelling techniques that can ensure that our potential evil plans have their intended consequences.