Maybe I'm not exactly the case you are asking for, but let me tell you my experience: I started college in '97 and specialized in robotics and AI. Dropped out

Maybe I'm not exactly the case you are asking for, but let me tell you my experience: I started college in '97 and specialized in robotics and AI. Dropped out during my fifth year (2003) for several reasons (some having to do with the university, others were personal/family related). My working experience begins in a startup in '99 doing web stuff. Now, in my country and in the early 2000's there were no jobs in robotics/AI, so I continued doing web stuff and, through the years I've moved up and down the ladder (I was development director of a multinational, left for a senior developer position because I was bored), lived in 4 countries and moved into different sectors and technologies. AI/Machine learning/Robotics were a hobby and I tried to keep up to date[0], but I had very few opportunities to apply that knowledge in my day to day. In terms of education, I'm a drop out: I went through five years of university and have more than enough university credits for a bachelor degree, but have never felt the need to go back and officially get a degree[1]. I started a master's degree in Ireland and left it after the second module[2]. Now, finally, the point I wanted to make (sorry for the long introduction, I felt it was important to give a bit of background): About five-six years ago, I got my first official position working full time with AI and machine learning[3] and suddenly found that my maths knowledge was definitely lacking. Even today, although I'm always improving, I find that when talking about deep learning, the maths are definitely my weak point even though I'm able to implement models, systems and tweak them enough to get good results. So, to answer your question: Yes, I keep being offered jobs. Maybe not as well paid as someone with a similar level of experience and a PhD and definitely not research-oriented. If the company does have a data science team, those jobs are usually working with them to take their models and integrate them with the rest of the product/s. [0] I went through Andrew Ng, Sebastian Thrun and Peter Norvig courses originally through Stanford Online and I'm constantly following one or two coursera or MITx courses in the area. I also have an account in Kaggle but I don't usually push my results, I'm more interested in the datasets. [1] I'd need to go back to my country and fight the bureaucracy there while trying to get documents from a university that no longer teaches computer science. [2] I felt a bit cheated, to be honest: The syllabus looked great, the content was mediocre at best and the papers we had to do had very little to do with the stuff we learnt and even with IT in general. 4K euros per module (for an online master) and the time spent wasn't worth it just to get an official piece of paper. [3] "Data science", I don't specially like that term and, if anything, I prefer to call myself a data engineer. I don't do science, I don't do research. I can take a research paper, implement it and add all the stuff that makes it useful and production-ready. But I don't call that science.