A Review of Signal Data Science
I took part in the second signal data science cohort earlier this year, and since I found out about Signal through a slatestarcodex post a few months back (it was also covered here on less wrong), I thought it would be good to return the favor and write a review of the program.
The tl;dr version:
Going to Signal was a really good decision. I had been doing teaching work and some web development consulting previous to the program to make ends meet, and now I have a job offer as a senior machine learning researcher1. The time I spent at signal was definitely necessary for me to get this job offer, and another very attractive data science job offer that is my “second choice” job. I haven’t paid anything to signal, but I will have to pay them a fraction of my salary for the next year, capped at 10% and a maximum payment of $25k.
The longer version:
Obviously a ~12 week curriculum is not going to be a magic pill that turns a nontechnical, averagely intelligent person into a super-genius with job offers from Google and Facebook. In order to benefit from Signal, you should already be somewhat above average in terms of intelligence and intellectual curiosity. If you have never programmed and/or never studied mathematics beyond high school2 , you will probably not benefit from Signal in my opinion. Also, if you don’t already understand statistics and probability to a good degree, they will not have time to teach you. What they will do is teach you how to be really good with R, make you do some practical machine learning and learn some SQL, all of which are hugely important for passing data science job interviews. As a bonus, you may be lucky enough (as I was) to explore more advanced machine learning techniques with other program participants or alumni and build some experience for yourself as a machine learning hacker.
As stated above, you don’t pay anything up front, and cheap accommodation is available. If you are in a situation similar to mine, not paying up front is a huge bonus. The salary fraction is comparatively small, too, and it only lasts for one year. I almost feel like I am underpaying them.
This critical comment by fluttershy almost put me off, and I’m glad it didn’t. The program is not exactly “self-directed”—there is a daily schedule and a clear path to work through, though they are flexible about it. Admittedly there isn’t a constant feed of staff time for your every whim—ideally there would be 10-20 Jonahs, one per student; there’s no way to offer that kind of service at a reasonable price. Communication between staff and students seemed to be very good, and key aspects of the program were well organised. So don’t let perfect be the enemy of good: what you’re getting is an excellent focused training program to learn R and some basic machine learning, and that’s what you need to progress to the next stage of your career.
Our TA for the cohort, Andrew Ho, worked tirelessly to make sure our needs were met, both academically and in terms of running the house. Jonah was extremely helpful when you needed to debug something or clarify a misunderstanding. His lectures on selected topics were excellent. Robert’s Saturday sessions on interview technique were good, though I felt that over time they became less valuable as some people got more out of interview practice than others.
I am still in touch with some people I met on my cohort, even though I had to leave the country, I consider them pals and we keep in touch about how our job searches are going. People have offered to recommend me to companies as a result of Signal. As a networking push, going to Signal is certainly a good move.
Highly recommended for smart people who need a helping hand to launch a technical career in data science.
1: I haven’t signed the contract yet as my new boss is on holiday, but I fully intend to follow up when that process completes (or not). Watch this space.
2: or equivalent—if you can do mathematics such as matrix algebra, know what the normal distribution is, understand basic probability theory such as how to calculate the expected value of a dice roll, etc, you are probably fine.
I suppose this might be better place to ask than trying to resurrect a previous thread:
What kind of statistics can Signal offer on prior cohorts? E.g. percentage with jobs, percentage with jobs in data science field, percentage with incomes over $100k, median income of graduates, mean income of graduates, mean income of employed graduates, etc.? And how do the different cohorts compare? (Those are just examples; I don’t necessarily expect to get those exact answers, but it would be good to have some data and have it be presented in a manner that is at least partially resistant to cherry picking/massaging, etc.) Basically, what sort of evidence E does Signal have to offer, such that I should update towards it being effective, given both E, and “E has been selected by Signal, and Signal has an interest in choosing E to be as flattering rather than as informative as possible” are true?
Also, the last I heard, there was a deposit requirement. What’s the refund policy on that?
Hello! I’m a cofounder of Signal Data Science.
Because our students have come into the program from very heterogeneous backgrounds (ranging from high school dropout to math PhD with years of experience as a software engineer), summary statistics along the lines that you’re looking for are less informative than might seem to be the case prima facie. In particular, we don’t yet have meaningfully large sample of students who don’t fall into one of the categories of (i) people who would have gotten high paying jobs anyway and (ii) people who one wouldn’t expect to have gotten high paying jobs by now, based on their backgrounds.
If you’re interested in the possibility of attending the program, we encourage you to fill out our short application form. If it seems like it might be a good fit for you, we’d be happy to provide detailed answers to any questions that you might have about job placement.
Wait, your category (ii) is surely exactly what we care about here. We want to know: For someone whose background would lead you not to expect high-paying data science jobs, is Signal effective in getting them a better chance of a high-paying data science job?
Yes, I see how my last message was ambiguous.
What I had in mind in bringing up category (ii) is that we’ve had some students who had a priori worse near term employment prospects relative to the usual range of bootcamp attendees, who are better positions than they had been and who got what they were looking to get from the program, while not yet having $100k+ paying jobs. And most students who would have gotten $100k+ paying jobs even if they hadn’t attended appear to have benefited from attending the program.
The nature of the value that we have to add is very much specific to the student.
One relevant consideration in such an evaluation is that Signal’s policies with respect to various things (like percentage of income taken, initial deposit, length of program) may have changed since the program’s inception. Of course, the program itself has changed since it started. Therefore, feedback or experiences from students in initial cohorts needs to be viewed in that light.
Disclosure: I share an apartment with Jonah Sinick, co-founder of Signal. I have also talked extensively about Signal with Andrew J. Ho, one of its key team members, and somewhat less extensively with Bob Cordwell, the other co-founder. ETA: I also conducted a session on data science and machine learning engineering in the real world (drawing on my work experience) with Signal’s third cohort on Saturday, August 20, 2016.
Well I got a job out of it.
As for statistics, they’re new enough that you’d want to wait a bit.
IMO Signal is worth the ~very little that you have to pay for it unless you already are getting job offers or already are very good with R (but then why do you want a bootcamp?)
They should have some statistics, even if they’re not completely conclusive.
As I understand it, the costs are:
$1400 for lodging (commuting would cost even more) $2500 deposit (not clear on the refund policy) 10% of next year’s income (with deposit going towards this)
I wouldn’t characterize that as “very little”. It’s enough to warrant asking a lot of questions.
How would you characterize the help you got getting a job? Getting an interview? Knowing what to say in an interview? Having verifiable skills?
Well, they taught me R and they helped me (along with some kind alumni) to go a bit further with neural networks than I otherwise would have. Having spent time hacking away at neural networks allowed me to pass the interview at the job I just got.
Knowing R caused me to get another generous offer that I have had to turn down.
Interview skills training with Robert was valuable, especially at the beginning. Robert seems to have a fairly sound understanding of how to optimise the process.
Well, that’s only a cost if (as in my case) you had to keep your normal home empty amd thereby double pay accommodation for that period.
Also some people on the course were local.
I was told that this is fully refundable if you don’t like the course within the first week, though I am not sure they would extend that to anyone (but you can ask).
I can answer the deposit one: Signal told me personally that they’d refund it in the first week if I wanted to quit due to it being a bad program. In reality it was good. I cannot guarantee that they’d extend this to anyone but you can ask.
What about after the program, if you don’t get a job, or don’t get a job in the data science field?
The deal I was given is that if you earn less than $40k for the next year, you get the whole program for free.
If you earn $lots as a painter, porn star, film producer—whatever—you still pay your 10% of what you earn above $40k capped at $250k. But if you plan on having a very lucrative non-data science career in the next year, then why are you on the program?
Just a quick update, I signed the contract today and am now employed in the role of senior machine learning scientist at a company in Europe.
Thanks for the review. I just submitted my application today (before I saw your post). I was a bit wary, due to fluttershy’s post you mentioned, but more because of the lack of results (ie actual job placements) on their website compared to more established programs. The main benefit I see to this program is being in a space with other people who you can easily bounce ideas off (ie, the social experience). I tend to work bettered in a structured environment, also. Its also good to hear that it is useful for networking as well. I wasn’t sure about that, because whereas other data science programs have working relationships with major companies, I didn’t get that impression when reading about Signal.
Signal do have contacts in a few high profile companies.
I suspect that the track record issue is somewhat a timing thing, but also somewhat because other bootcamps are quite good at creative statistics to cook up their 90% figures.
For example, I started a springboard data science course with a monthly fee, but pulled out when I realised it was useless. However they will not count me as a “fail”, because I didn’t complete.
The mentor they assigned to me at springboard just told me to go Google everything, and their curriculum was not as good, you were left to fend for yourself with no help.
Contrast Signal where you’re actually there and get help when you’re stuck.