May 04 to 05 2015, Santa Clara, USA.


Speaker "Esteban Arcaute" Details

Name :
esteban arcaute
Company :
Title :
Topic :

The role of data scientists in product development

Abstract :

How Many Data Scientists Does it Take to Build a Data Product? In 2012, D.J. Patil, the newly appointed U.S. Chief Data Scientist, claimed that the sexiest job of the 21st century would be that of the “data scientist”. While there seems to be a never-ending thirst for data science professionals, a simple question remains difficult to answer – do I need a data scientist to develop products that rely on data science techniques? And if so, how many? Will I need them once the product is launched? In this talk we consider the above questions by examining the role of the data scientist in the product development and maintenance lifecycle. We first define the unique skills that distinguish data scientists from other data professionals. We then explore where said skills can be best utilized when developing a data product. We do so by considering the existing underlying infrastructure. Finally, we explore when and how to involve data scientists post-product launch.

Profile :
Esteban D. Arcaute was born in Mexico City, and earned a Ph.D. and a M.S. from Stanford University in Computational and Mathematical Engineering. He also holds two other masters, one in Electrical and Computer Engineering from Supeléc (France) and one in Applied Mathematics from the Université de Metz (France). He is currently the Sr. Director and Head of Data Science, Category Development, at @WalmartLabs. Prior to that, he was at Adchemy Inc. (acquired by @WalmartLabs) where he held several positions, from Research Scientist, to Sr. Director and Head of Research. Esteban has been actively working on the foundations of electronic commerce since 2005, first as an academic researcher, publishing over 10 peer reviewed publications with over 15 researchers; then as an industrial researcher and thought leader. His current interests span from learning and control systems with a human in the loop, to advanced analytics and experimentation.

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