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I went from chemical engineering into data science, and I wonder this constantly. Everything about chemical engineering was much more difficult (at least what

I went from chemical engineering into data science, and I wonder this constantly. Everything about chemical engineering was much more difficult (at least what you would be expected to do in a typical job; exceptions apply). I really miss the hard sciences, but I also really do not want to take a 4x pay cut. Also, I'm not sure about the supply and demand argument. The typical ask for a data scientist is much simpler than specialized ChemE knowledge; supply should have ramped up so quickly that comp would have fallen to typical engineering salaries long ago if that were the case.

lotsofpulp 4y ago
> Also, I'm not sure about the supply and demand argument. The typical ask for a data scientist is much simpler than specialized ChemE knowledge; supply should have ramped up so quickly that comp would have fallen to typical engineering salaries long ago if that were the case. I would question my assumptions before disputing the function of supply and demand curves.
colinmhayes 4y ago
There aren’t any people over the age of like 35 who started their career in data science. Careers are sticky, people don’t like switching once they’re in one. They’re being trained quickly and I think you’re right, the salary used to be higher than a normal software dev but that doesn’t seem to be the case anymore.
- runnerup 4y ago
  More like no one hires you into a new career after 35. I’m 34 now and it was hell getting into software engineering from chemical engineering even with good project experience and acing leetcode.
  - visarga 4y ago
    I switched from full stack to ML at 38. I was preparing for a few years by doing courses, personal projects and following new papers as they come up. When I got hired there was no issue with the fact that I was self trained - they have been interviewing for 6 months and failing every candidate by then. Soon after I got hired I was myself part of the interviewing committee and saw the hiring situation first hand - most candidates can't program their way out of a shoe or explain how the most commonly used neural net layers work. I mean, I had one who couldn't open a TXT file in 30 minutes, the data file he was supposed to use in the problem.
- mint2 4y ago
  Same, I miss Cheme and actually doing work on physical systems. But applied DS is more lucrative and so much more flexible in work location. DS is way easier although the stats and programming does throw many people off
theskypirate 4y ago
There is a severe oversupply of engineering graduates in the US, that's all there is to it. All hardware engineering jobs have been colocated with the actual manufacturing facilities they are designing for – i.e., Asia-Pacific. Even the reduced number of graduates is too many, because the demand is virtually zero. People are not dying and retiring as fast as the industry itself is.

lotsofpulp 4y ago

> Also, I'm not sure about the supply and demand argument. The typical ask for a data scientist is much simpler than specialized ChemE knowledge; supply should have ramped up so quickly that comp would have fallen to typical engineering salaries long ago if that were the case. I would question my assumptions before disputing the function of supply and demand curves.

colinmhayes 4y ago

There aren’t any people over the age of like 35 who started their career in data science. Careers are sticky, people don’t like switching once they’re in one. They’re being trained quickly and I think you’re right, the salary used to be higher than a normal software dev but that doesn’t seem to be the case anymore.

runnerup 4y ago
More like no one hires you into a new career after 35. I’m 34 now and it was hell getting into software engineering from chemical engineering even with good project experience and acing leetcode.
- visarga 4y ago
  I switched from full stack to ML at 38. I was preparing for a few years by doing courses, personal projects and following new papers as they come up. When I got hired there was no issue with the fact that I was self trained - they have been interviewing for 6 months and failing every candidate by then. Soon after I got hired I was myself part of the interviewing committee and saw the hiring situation first hand - most candidates can't program their way out of a shoe or explain how the most commonly used neural net layers work. I mean, I had one who couldn't open a TXT file in 30 minutes, the data file he was supposed to use in the problem.
mint2 4y ago
Same, I miss Cheme and actually doing work on physical systems. But applied DS is more lucrative and so much more flexible in work location. DS is way easier although the stats and programming does throw many people off

theskypirate 4y ago

There is a severe oversupply of engineering graduates in the US, that's all there is to it. All hardware engineering jobs have been colocated with the actual manufacturing facilities they are designing for – i.e., Asia-Pacific. Even the reduced number of graduates is too many, because the demand is virtually zero. People are not dying and retiring as fast as the industry itself is.