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Machine learning effectively didn't exist a decade ago. A decade from now, it's likely to be where building HTML pages was in the nineties, or database-backed web applications in the 00's. I understand it's a deeper skill set, but depth has little to do with supply-and-demand. Physics, biology, and similar have a lot of depth, and the fundamentals evolve much more slowly and take years to truly understand and be able to apply them effectively as well, but employment prospects are grim. If blockchain had turned out to be the Next Big Thing, the important fundamentals would have been in cryptography. And so on. Someone young, without family, mortgage, etc. obligations, will be able to get into the current hot field much more quickly than a 40-year-old or 50-year-old with three kids in school and possibly starting medical problems. It doesn't help that there is massive age discrimination. If you want to be employed older, the trick seems to be to move into a cross-disciplinary role, such as management (people+tech). A lot of other cross-disciplinary roles will do, though (medicine+tech, bio+tech, chemistry+tech, EE+tech, etc.). Pure tech doesn't seem to cut it after thirty for career growth, after forty for job stability, or after fifty for having a job at all. |
The star researchers who command top compensation in the field today often have over a decade of experience.
I agree that a much larger pool of graduates might dampen average compensation in the future somewhat. A key distinguishing feature of these more complex skills (relative to HTML, etc) is that much fewer percentage of people are capable of mastering them, and it takes longer commitment as well.
Relative to pure physics and biology, the applications are much broader and thus better prospects for the experts.
Do senior petroleum engineers face the career issues you suggest?