Comment by tjpaudio

This is an awesome analysis of the situation. Some things I have noticed as a data scientist of 4 years so far: - Increasingly, data scientist is just being used in place of senior analyst because it attracts more applications. - At the firms I've worked that are software tech companies, there was an outsized interest in mid-level software engineers wanting to be data scientists, mostly because the career development prospects at that stage are grim and data science usually means a pay bump. This demand has had the opposite effect - software shops are leery of promoting engineers to data scientists for fear of inciting contention among the ranks. - Building on the data scientist usually means senior analyst, it has also come to mean analyst that can build their sql query into a scheduled ETL or daily process of some sort. You work in pandas instead of excel sorta thing. - I have personally gotten all my data science jobs from talking about the business side of things. I think engineers approaching the field from a hard-skills perspective is totally wrong. My last technical take home was in a language I had never used before and likewise my execution was shitty, but I was able to well explain the problem, how the data could be used to predict the variation, and how the data science product fit into the business. I got an offer before I left the building.