I'm coming at this as an academic, and the problem I'm hearing from companies about the whole idea of a "data scientist" is that it describes a superstar -- som

I'm coming at this as an academic, and the problem I'm hearing from companies about the whole idea of a "data scientist" is that it describes a superstar -- someone who knows math, statistics, programming, the business domain, etc, and is self-sufficient. The glowing articles about data scientists focus on the talents and skills they have, and don't tell us much about the operational "work" they do. I can't tell from the literature, for example, what kind of workflow I'd see on a kanban or scrum taskboard for a data science team. Closer to home, I am also very interested in how a university can train students to do this kind of work... so I want to understand the operational processes and not just a list of technologies the students should learn. I'm currently teaching a course on software development which touches on workflows and DevOps, and I'd like to do the same for our new analytics major.