Putting data science in practice is hard. But after years of trying different ways to do it, we believe to have learned which traits help the most. One of these traits is "Fail fast to learn fast", and I will be doing just that with this talk. The presented traits might not be complete or can be outright wrong in your perspective! I hope you'll join to improve and learn together
The talk is aimed at everyone that wants to learn how to put data science in pracrtice more effectively. The traits can help individual contributors, collaborating teams or even organisations that are looking to become more effective in how they organize. Sharing these traits will hopefully speed up your development as a data science enthusiast.
The talk will touch on the following topics:
In the highlighted examples I will talk about two use case from personal experience. In the first, I'll talk about how we introduced a paradigm shift in how we create and use data driven forecasts to improve how we operate many processes across bol.com. In the second, I'll share the approach taken to help governmental agencies make better use of data to predict COVID outbreaks and enable them to adopt their strategy using novel techniques and data sources.
The following traits will be presented and highlighted (in rough order):
The talk will be supported with with real time feedback from Menti and encourages feedback from the audience. This list was compiled based on many iterations and lots of feedback, and will definitely change after this session once again. I'm hoping you'll help and further refine the list for future sessions.