Since I’ve talked to several of the people involved (Jonah and two students), and I’m a data scientist, I figured I should weigh in.
It seems to me like data science, like programming, is mostly about thinking clearly, and so it’s in some sense unsurprising that people could be trained to do it quickly, assuming that they start off thinking clearly and just need to learn specific techniques. But while this is somewhat true for programming, it seems less true for math (and statistics as a branch of math)--I would not expect, say, actuarial boot camps to be a reasonable thing.
My standard bootcamp advice also applies—the value of a programming bootcamp, for example, is that it gets you from 0 job offers to 1 job offer, and so it may be worthwhile to do the interview process first, and ensure that you actually need a bootcamp to get hired. (This is somewhat dangerous since most companies will only look at candidates once per year, and so if you don’t get hired, do a three month bootcamp, and then try to get hired again, you may need to wait ~9 months.)
It’s also worth pointing out that the better employers are mostly looking for quantitative PhD types; I was recently approached on LinkedIn by someone who is about to graduate from a one-year masters program focused on data science and I was reluctant to recommend that he apply to where I work because it was unclear he would pass either our HR filters or our technical interview process. (And if I’m reluctant to recommend him, I’m also reluctant to recommend anyone from Signal.)
But that said, there are a bunch of companies out there who need some sort of data science work, and there are multiple gradations of it. Lots of companies have many more ‘analyst’ roles than they do ‘scientist’ roles, and I would expect people who can make it through Signal to have a good shot at those. (Similar bootcamps boast high placement rates, but if you look at the sort of roles they mention, many of them are ‘data analyst’ or ‘software engineer’ roles that I would be reluctant to call “data science” but that may be because I take a fairly narrow view of the term, as a job description. If a software engineer goes to a bootcamp and gets a software engineer position afterwards, it’s not clear whether or not that reflects a success.)
Be aware that the instruction will be fairly self-driven, and that you’ll mostly get instruction on the level of “this is how you would find that answer” instead of “this is the answer,” and if you’re looking for the latter you should probably look elsewhere. (For example, instead of fixing a particular error, expect to be taught how to read error messages and Google them, which is overall a more useful answer.)
Also be aware, as mentioned earlier, that the value of a bootcamp is getting people from 0 offers to 1 offer, and until the first cohort has finished their job search, how effective Signal is at that remains unknown.
TL;DR: I can’t feel comfortable recommending Signal until they have a proven track record, but talking with people involved has put my worries to rest. If you think you’d be a good fit for the environment at Signal (and the best way to figure this out is probably talking with Jonah) and you estimate the improvement in career prospects is worth the cost, go for it.
Since I’ve talked to several of the people involved (Jonah and two students), and I’m a data scientist, I figured I should weigh in.
It seems to me like data science, like programming, is mostly about thinking clearly, and so it’s in some sense unsurprising that people could be trained to do it quickly, assuming that they start off thinking clearly and just need to learn specific techniques. But while this is somewhat true for programming, it seems less true for math (and statistics as a branch of math)--I would not expect, say, actuarial boot camps to be a reasonable thing.
My standard bootcamp advice also applies—the value of a programming bootcamp, for example, is that it gets you from 0 job offers to 1 job offer, and so it may be worthwhile to do the interview process first, and ensure that you actually need a bootcamp to get hired. (This is somewhat dangerous since most companies will only look at candidates once per year, and so if you don’t get hired, do a three month bootcamp, and then try to get hired again, you may need to wait ~9 months.)
It’s also worth pointing out that the better employers are mostly looking for quantitative PhD types; I was recently approached on LinkedIn by someone who is about to graduate from a one-year masters program focused on data science and I was reluctant to recommend that he apply to where I work because it was unclear he would pass either our HR filters or our technical interview process. (And if I’m reluctant to recommend him, I’m also reluctant to recommend anyone from Signal.)
But that said, there are a bunch of companies out there who need some sort of data science work, and there are multiple gradations of it. Lots of companies have many more ‘analyst’ roles than they do ‘scientist’ roles, and I would expect people who can make it through Signal to have a good shot at those. (Similar bootcamps boast high placement rates, but if you look at the sort of roles they mention, many of them are ‘data analyst’ or ‘software engineer’ roles that I would be reluctant to call “data science” but that may be because I take a fairly narrow view of the term, as a job description. If a software engineer goes to a bootcamp and gets a software engineer position afterwards, it’s not clear whether or not that reflects a success.)
Be aware that the instruction will be fairly self-driven, and that you’ll mostly get instruction on the level of “this is how you would find that answer” instead of “this is the answer,” and if you’re looking for the latter you should probably look elsewhere. (For example, instead of fixing a particular error, expect to be taught how to read error messages and Google them, which is overall a more useful answer.)
Also be aware, as mentioned earlier, that the value of a bootcamp is getting people from 0 offers to 1 offer, and until the first cohort has finished their job search, how effective Signal is at that remains unknown.
TL;DR: I can’t feel comfortable recommending Signal until they have a proven track record, but talking with people involved has put my worries to rest. If you think you’d be a good fit for the environment at Signal (and the best way to figure this out is probably talking with Jonah) and you estimate the improvement in career prospects is worth the cost, go for it.