I was a comp science graduate , graduated almost 20 years ago.

I learnt about AI back then when AI wasn't popular at all.

Then suddenly Netflix ran a context to see who can best predict the consumer's watching behaviour and Data Science flew off ( Using random forests, ensemble technique etc etc )

and everyone's calling themselves Data Scientist , Chief Data Officer , whatever fancy name you can think of and I do resonate with some forumers here who mentioned about those position taken up by pple who doesnt know a single thing about data or technicals at all.

Not to say I am a genius of sort , but I do think there are certain disservice to a true data scientist, true data engineer, true chief data officer, if you put some one who are good at telling stories without much technical or statistical background to head a team. The team will eventually implode and these true data engineers/scientist will be demoralized and company doesnt get any value of out their investments.

Having said that, some bigger companies set up the team for experimental purposes just to see what it does , or to a certain extent, bragging rights, cause they can. So its a sad stage where you see all these top level buffoons who knows how to present and sell , but technically jack sheet or mathematically idiotic just to understand basic probability concept.

Well , that is just how the industry works, and how company politics works , but the silver lining is you see nowadays , top companies are pushing more enginnering/technical background to the top job ( , ie Satya Nadella who is a technical guy , vs Steve Balmer, a sales guys, and look at the share price. Hope this decade , we can see more true engineers/technical rise to the top.

Also , i got my hands dirty to understand data science , and I realised the most basic thing is to understand statistics first, before anything else, and of course, to have deep knowledge in your domain area , then only you can truly apply what you learn in data science, to solve your industry challenges.