Doing a PhD in data science / machine learning after a PhD in civil engineering I am about to finish my Ph.D. in civil engineering, I would finish it by the age of 28.
I don't like my field that much and was pushed to pursue it from the beginning (at that time, was very confused and did not know what I want / I need and that is a huge problem in my personality, so my father pushed me to pursue it even though I did not like it at all !).
(one could ask why did you pursue a PhD in a field you don't like; the answer is pretty simple; it was the only way to get out of a third-world country :D)
seeing the big-fat salaries of data scientists/machine learning engineers around the world makes me jealous sometimes and makes me super unsatisfied with the work/research and the field I am pursuing.
I am really considering getting some undergraduate courses once I finish my current Ph.D. and start applying for CS masters. I will try to apply for double grants also, don't know if my current Ph.D. could help get those grants which will make me financially comfortable pursuing research in other fields again.
Also, I want to pursue a Ph.D. in machine learning cause I see the salaries are fatter for those dudes; I don't like academia and I don't like research and I really do hate teaching but I am used to doing a lot of things I don't like.
What are your perspectives?
I will agree with the commentators who say that one PhD is enough. I am sure you can start applying ideas from machine learning in your field (civil engineering) and perhaps after a while even move to a completely different field. PhD is essentially a qualification that demonstrates your ability to engage in abstract learning and research. You don't need two of these degrees to doubly-certify yourself. If you feel that you are lacking in certain aspects of knowledge related to machine learning or data science, find collaborators in these fields -- that's way more efficient than taking classes (and more productive in terms of research output).