Coming out of university with a BS, graduates today are far from well-equipped to perform in corporate upper middle-class jobs (the jobs promising upward mobility). I think this has most to do with an increase in the amount of data companies deal with. White-collar employees need to know not only the ins-and-outs of their industry, but they must also know how to use increasingly complicated enterprise software, and possess more advanced analytical skills to operate with more complicated data. As a result, graduates with a 4year degree are stuck for 5+ years in internship limbo. Companies will bleed money training interns who literally can't offer anything of value and instead will use up the work hours of the skilled employees who train them. Hence, <30k salaries.
I think this is why there is a trend for the more math-heavy STEM fields to flee the coop earlier --they spend less time on the software and analytics training to become valuable sooner.
Certain degrees like health, or design are unlike general STEM fields in that they train students for specific technical jobs rather than teaching broader critical thinking/problem solving. So, they get jobs right out of school (5year engineering programs...?).
PhD's are in the best position to flee the coop quickly because they are paid a livable wage (in most cases) while in graduate school. It's also not terribly difficult to get into a PhD program (completing it is another story). After receiving their doctorate, PhDs rely on tight-knit academic networking within their field of study to do their post-doc. However, this is where many of them get stuck, receiving a salary <70k (often far <). Increasing competition for faculty positions has pushed many a post-doc out of academics (though, by this time I feel they can compete well in the corporate sector).
What I can't explain is law students. I thought there was a bubble leaving most of them jobless. I presume that maybe a law degree is relatively more helpful in scaling the world of big-data (and 'big-regulation') making them prime pickings for corporate jobs earlier than the rest.
Coming out of university with a BS, graduates today are far from well-equipped to perform in corporate upper middle-class jobs (the jobs promising upward mobility). I think this has most to do with an increase in the amount of data companies deal with. White-collar employees need to know not only the ins-and-outs of their industry, but they must also know how to use increasingly complicated enterprise software, and possess more advanced analytical skills to operate with more complicated data. As a result, graduates with a 4year degree are stuck for 5+ years in internship limbo. Companies will bleed money training interns who literally can't offer anything of value and instead will use up the work hours of the skilled employees who train them. Hence, <30k salaries.
I think this is why there is a trend for the more math-heavy STEM fields to flee the coop earlier --they spend less time on the software and analytics training to become valuable sooner.
Certain degrees like health, or design are unlike general STEM fields in that they train students for specific technical jobs rather than teaching broader critical thinking/problem solving. So, they get jobs right out of school (5year engineering programs...?).
PhD's are in the best position to flee the coop quickly because they are paid a livable wage (in most cases) while in graduate school. It's also not terribly difficult to get into a PhD program (completing it is another story). After receiving their doctorate, PhDs rely on tight-knit academic networking within their field of study to do their post-doc. However, this is where many of them get stuck, receiving a salary <70k (often far <). Increasing competition for faculty positions has pushed many a post-doc out of academics (though, by this time I feel they can compete well in the corporate sector).
What I can't explain is law students. I thought there was a bubble leaving most of them jobless. I presume that maybe a law degree is relatively more helpful in scaling the world of big-data (and 'big-regulation') making them prime pickings for corporate jobs earlier than the rest.