As many have said here, and as a working and apparently in-demand data scientist, I agree that the tricky part about data science is that being effective isn't

As many have said here, and as a working and apparently in-demand data scientist, I agree that the tricky part about data science is that being effective isn't a matter of just any one thing. You have to be a unicorn of sorts who is, above all things, capable of solving any problem which comes your way. You have to be exceptionally flexible and very scrappy. There are a lot of people who know more about modeling, software engineering, statistics, machine learning, analytics, and so on than I do. But I excel at bringing everything together and solving difficult business problems. It's really difficult to train someone to be this way. It takes a lot of time, experience, skills, and a unique disposition to be an effective data scientist. At least to be the kind of data scientist I am. And I'm still early in my career. Just my two cents. I suspect there will continue to be a glut of people who, on paper, have the data science skills, but lack all the intangibles. Who knows, maybe the various programs and boot camps will start doing business scenario learning: here's a tough real world problem where we don't tell you how to solve it, but we desperately need you to figure it out. Go!