I always enjoyed helping students, undergraduate and graduate, get jobs. Most professors have never been gainfully employed and send students (out of disinterest if not incompetence) to equally clueless ‘academic advisors’ and ‘placement directors’. Now that I’ve left the professorate, one of my proudest accomplishments is having helped several people— on Twitter and in real life— secure nonacademic jobs, and by popular demand I’ve decided to share whatever wisdom into the process I can. I am writing this mostly with graduate students in the social sciences and related fields who want to pursue a career in ‘data science’ in mind.
Thanks for the post- I've been wondering when you planned to elaborate on the typology of data jobs you proposed.
I'm an undergraduate student studying economics, and I'm looking to become a strategy consultant once I graduate. I'm well aware of your opinions on consultants, but my goal when entering the workforce is to find a job where I can use my social sciences training to parse data in a way relevant to corporate clients, which would be more of an Astrologer job. Do you have any tips on what I can do to find a place to work that's large enough that I can use the name as a springboard for my career, but not so moribund that I get sucked into their Data Nigger plantations and eventually emerge with no motivation or marketable skills?
Working for a Mediocre is often underrated for many of the reasons you describe. Being a technical expert at a Mediocre can give you some amazing work life balance.
On the other hand I wonder sometimes how safe some of the data roles are when costs get tight—I would never, ever want to work in sales because it’s literally illegal not to be gay in sales, but where I work for example the sales folks are the golden children because they bring revenue, and that helps shield them from downturns somewhat.
So incredibly accurate in so many ways and I wish I could share it to the rest of my team who have to enable an entire platoon of these people as their primary job. Alas.
It was very interesting to read this having basically no knowledge about data science (beyond a Bachelor's course in Sociology) or the corporate world at all. It's remarkable how the market in data science works compared to other historic fields.
“When an incantation becomes a KPI, it ceases to be a good incantation” -goodhart’s law
Thanks for the post- I've been wondering when you planned to elaborate on the typology of data jobs you proposed.
I'm an undergraduate student studying economics, and I'm looking to become a strategy consultant once I graduate. I'm well aware of your opinions on consultants, but my goal when entering the workforce is to find a job where I can use my social sciences training to parse data in a way relevant to corporate clients, which would be more of an Astrologer job. Do you have any tips on what I can do to find a place to work that's large enough that I can use the name as a springboard for my career, but not so moribund that I get sucked into their Data Nigger plantations and eventually emerge with no motivation or marketable skills?
Working for a Mediocre is often underrated for many of the reasons you describe. Being a technical expert at a Mediocre can give you some amazing work life balance.
On the other hand I wonder sometimes how safe some of the data roles are when costs get tight—I would never, ever want to work in sales because it’s literally illegal not to be gay in sales, but where I work for example the sales folks are the golden children because they bring revenue, and that helps shield them from downturns somewhat.
So incredibly accurate in so many ways and I wish I could share it to the rest of my team who have to enable an entire platoon of these people as their primary job. Alas.
Can't wait for the next parts.
It was very interesting to read this having basically no knowledge about data science (beyond a Bachelor's course in Sociology) or the corporate world at all. It's remarkable how the market in data science works compared to other historic fields.
Lmaooo, I'm laughing so hard