Why Data Science Fails

Friday, January 19, 2018 - 1:25pm - 2:25pm
Lind 409
Scott Ernst (When I Work)
We hear stories of data science successes all the time, but stories of data science failures are becoming more common as well. As hype gives way to reality, businesses are increasingly scrutinizing their data science investments. But why do some teams succeed while others fail? We’ll dive into the key attributes that set success apart from failure using a framework that originated in the aftermath of the dot-com crash and helped guide companies like Facebook, LinkedIn, YouTube, Reddit, Zillow and Twitter.

Scott is currently the Director of Data Science & Data Engineering at When I Work, a Minneapolis-based startup. He has a PhD in computational physics that focused on large-scale astrophysical and magnetohydrodynamic plasma simulations. Over the last decade Scott has worked in various data science and engineering roles, which included leading the data science team for an international research project modeling dinosaur behavior on the world’s largest dinosaur track-site. He has also worked as a data visualization artist, creating 3D digital visualizations for clients all over the world including National Geographic, National Public Radio (NPR), Carnegie Natural History Museum, Los Angeles Natural History Museum, Asahi Shimbun (朝日新聞), Tokyo Natural History Museum and Jurassica in Switzerland.