From a data scientist that has been working as an architect for data systems for some time now, the way that data science was done 2 years ago changed considerably to how we do data science and design data systems geared to machine learning today. Data can be the "fuel" the economy, but the extreme demand for data scientists that need to know a huge number of things, from statistics do machine learning to programming, databases and so on, is reducing, and more specialized roles, like machine learning engineer, is growing. That´s the reason for my comment: the bubble of data scientist highly skilled over a vast number of areas is dying, and data scientists need to start to specialize to survive.