61–70 of 122 posts
>. A big thing about the transition to tech is that you possibly start communicating with people who don’t really know what a vector space is. Be ready to have those conversations. Honestly ask yourself if you’re OK with having those conversations. This is so snobbish. What here is even think about ?
I was a PhD student in mathematical logic, and I know a couple people who got PhDs in this area and became data scientists. One thing about this field (and other areas of math) is that almost everyone in it feels mediocre. It's like 10% of the people are 10x better than the other 90%, 1% are 10x better than the next 9%, .1% are 10x better than the next .9%, etc. The top two people in the field seem to be notably bett…
One side of this that bugs the crap out of me: I have a PhD in math and, after getting sick of teaching mediocre students with a palpable aversion to mathematics, I spent a couple of years applying for data science jobs and getting very few responses. The few interviews I got seemed to go well, but I had no offers and gave up on leaving academics. I have experience in software development (C++), I have a portfolio of…
I'd suggest figuring out which niche of data science most aligns with your personal interests and start there. Hiring managers don't discriminate based on "too many years in academia", it's more what's the reason they should hire YOU over candidate y?
Diehard animal lover? I bet the Sierra Club would love a statistician who could help them quantify how many elephants are being poached in Africa per year.
Interested in sports? Strava gets millions of data points a day, I'm sure they're looking for help finding signals in the noise.
Can't get enough of financial markets? Finance jobs all over the place for quants.
If your profile is too generic they'll see no good reason to hire you, but if you're passionate about X it can really work in your favor.
The job search is depressing but never give up hope.
One side of this that bugs the crap out of me: I have a PhD in math and, after getting sick of teaching mediocre students with a palpable aversion to mathematics, I spent a couple of years applying for data science jobs and getting very few responses. The few interviews I got seemed to go well, but I had no offers and gave up on leaving academics. I have experience in software development (C++), I have a portfolio of…
It's never too late to switch. I'd suggest figuring out which niche of data science most aligns with your personal interests and start there. Hiring managers don't discriminate based on "too many years in academia", it's more what's the reason they should hire YOU over candidate y? Diehard animal lover? I bet the Sierra Club would love a statistician who could help them quantify how many elephants are being poached i…
What about the other way around? I'm from an engineering background, going in the direction of data scientist. Sometimes I find that my math skills could be stronger, and I try to read up on things when I encounter them, but still it sometimes feels like there is an infinite amount to learn. Maybe I could use some more systematic approach to it. Anyone else who has walked this path, and could come with some useful ad…
Check out the syllabuses and self-study at your own pace
Earlier quoted context omitted.
A data scientist is an engineer.
Can you elaborate as to why and how? Im genuinely curious. :)
What matters is not how elegant your solution is, what matters is solving the problem. And doing it under cost and time constraints.
An engineer is first and foremost, a person focussed on the end goal, above all else.
Earlier quoted context omitted.
A data scientist is an engineer.
"Mathematicians becoming data scientists..." At best you're talking about a career change, at worst you're talking about a watered-down version of your intended career.
I was a PhD student in mathematical logic, and I know a couple people who got PhDs in this area and became data scientists. One thing about this field (and other areas of math) is that almost everyone in it feels mediocre. It's like 10% of the people are 10x better than the other 90%, 1% are 10x better than the next 9%, .1% are 10x better than the next .9%, etc. The top two people in the field seem to be notably bett…
A lot of these "arcane" topics have long-term horizons. Agree with everything else but the whole point of research is to probe the space of possibilities (theoretical and practical) to find major ideas. Most of them fail but that's part of the exploratory process - it's expected.
Earlier quoted context omitted.
Can you elaborate as to why and how? Im genuinely curious. :)
An engineer is a person who creates real world solutions to real world problems. What matters is not how elegant your solution is, what matters is solving the problem. And doing it under cost and time constraints. An engineer is first and foremost, a person focussed on the end goal, above all else.