Thread by @realscientists

Probably my last thread on RealScientists (but hmu if you’d like to hear more about anything).

*Personal* observations between academia (physics, astro) and the tech industry (data, product).

https://twitter.com/realscientists/status/1372901544543277060

1. Job scarcity & security.

I often compare early careers in academia to professional sports, specifically minor league baseball. They’ll take a look at the schools you played at, your overall stats, maybe they’ve seen you give a talk or two.

If you had a good year or two, maybe people talk about you. Just had a bad year? Pass.

A handful of people will get the “golden ticket,” a stable, long-term arrangement. Most will get a string of 2-year deals, shuttle to-fro between “big leagues” and “minors” before leaving.

And good luck getting to pick the city (or even the country) where you work.

In contrast, there are way more possibilities for tech jobs. (after you break in… getting your foot in the door is the hardest part, no doubt.)

There’s a quote about the tech industry, “There’s a war for talent, and talent won.”

Established tech workers can ask for (relatively speaking) the moon in compensation, because their work can generate so much profit, and there’s competition for their services.

I’ve seen tech companies take the stance, “Even if we don’t have a role for a stellar candidate now, try to get them aboard and figure out the rest of the puzzle later.”

And even w/out the difference in compensation, just knowing that the job is yours, there’s no ticking clock for the appointment, that there are many other jobs you have real shots at… removing that piece of anxiety about timing, security, location was absolutely life-changing.

I mean, yes. Businesses fail, people lose their jobs. But tech is a relatively privileged sector when it comes to job security.

Everyone should have that and we should work toward that.

Career flexibility, too.

It’s a bit trickier to change or broaden your specialty pre-tenure. Whereas in industry, it’s much easier to look for (or craft your role to be) something that’s more toward product or data engineering, or toward different kinds of data problems.

2. Diversity, Equity, Inclusion.

Neither academia nor tech really get it. There are people who are woke, but as institutions, they’re failing.

At a lot of places, it’s a bunch of well-meaning white+Asian people trying to do DEI while their organizations resist bold changes.

(I started the DEI initiative at one of my stops in tech… oof. Lots to unpack there.)

Right now, neither space is built for *everyone* to have equal access and thrive. 😞

A lot of circular problems in the network-driven ways in which companies and universities hire, and the bias toward “prestige” of the candidates’ past stops.

https://twitter.com/astrobassball/status/1364218926259990528?s=20

3. Workplace culture

There’s a definite temperature difference. Yes, it depends on the field & specialty, public vs. startup vs. in-between.

But in my experience, academia is more “Asian parent” of the two.

There's a lot more "Yup, this will work. Now do more" in academia, and more "Oh this is amazing. Thank you so much!" in industry.

There's more open appreciation and validation: "We all appreciate everything you do." "I want to give a shout-out to A for making this possible."

If you read my mega-thread earlier today, it was super important and memorable for my advisor to say that I'm a "good student."

We all deserve that and more, and I've definitely found it more outside academia.

And I'm sure that all the job security stuff has a lot to do with that. Less competition, fewer temporary positions, better work-life balance…

4. Work-life balance

Tech isn't some paradise. Work-life balance seems better overall, but there are some companies and industries with longer hours, and I've definitely been around "VIP needs this in an hour" and "work around the clock for project deadline."

But I've also been around people who believe, "If we have a down year in output and my team is happy, I'll take that over other way around."

I also know a lot of people who make up a "new guard" of academic mentors, working to change their deps & collaborations for the better.

One thing I'll note is that when I had a bad publishing year in academia (a handful of Nth-author papers + frustrated bosses), I felt completely f**ked.

I thought it was hard to rebound from that when you're applying to academic jobs, because there're N>>1 others w more papers.

Whereas in industry, people seem more understanding of bad fits or rough personal years. More positions to fill + they're often just happy to find a good fit for their team.

Again, this is personal experience & perception only, and others will surely have had different stories.

I'm happy with the way things turned out.

I know others who feel the same way; but also those who feel like tech / data has not been the right space for them, who really miss the intellectual & other rewards of academia.