As a statistician now working as a machine learning engineer, my response is “definitely not”. It’s all the frustrations of software development, but on top of that you are now frequently dealing with clients/colleagues whose requests are now not simply impractical, but usually defy the laws of mathematics and probability, and an ever present pressure to put out work that amounts to fraud. Analytics have a lot of value to provide many organizations, but it requires planning, foresight, and a willingness to sacrifice a little now for the sake of a payoff in insights later, which very few organizations have, in my experience. So it essentially becomes a buzzword and people throw worthless data at you to wave a magic wand over so you can tell them what they want to hear. Doing so would essentially require lying, so instead, we would perform the awful, worthless analysis, it usually didn’t provide much insight, and we would include a litany of disclaimers about why the little insight it did provide wasn’t al that trustworthy, which would just disappoint and infuriate the people we were working with. We would also provide detailed guidance on how to execute moving forward to make the process much more valuable the next time around, which without fail went in one ear and out the other.
So essentially we became figureheads. Our work rarely was used in any significant way or provided much value, but we were kept around because the company wanted to be able to tout its “data driven” culture.
It was so bad that at one company I worked for, they had the data science/analytics department start putting on a yearly intracompany conference on analytics that became a huge deal. One year they got Stephen Levy, the author of Freakonomics, to be the keynote speaker. At one point he shared a story about how he was consulting with a company on their marketing, and they found that they had accidentally not been running ads in a particular metro area, and were able to leverage this to act as a control to assess the materials effectiveness. But when asked to intentionally do something similar moving forward, the company balked. It was so close to home that my colleagues and I wondered if the head of our department had fed him the need to talk about it. And yet, not a single thing changed at the company during my time there.
I currently work in a role much closer to software engineering, and I have all of the same problems described by the person in the original post and that many are describing here. But I consider it a strict upgrade over my time working as a statistician.