I've noticed that there is a great number of interviewers that do not take the initiative to just be nice. I suppose they just forget that the interview process is a two-way street.
I've had good experience with http://angel.co though you have to be careful since there are recruiting agencies that scour that site as well. In NYC there is also http://interviewjet.com, http://hired.com, and http://underdog.io. These all pretty much have a similar model where you can have be in the highlight with a handful of other engineers sent to a whole lot of companies at the same time.
I've met a bunch of folks who changed careers and are doing full-time development now. A fair amount of them went through one of those devlopment bootcamps like Recurse Center (ex-Hacker School). The other folks basically got their foot in the door through networking.
So, I'd say those would be a couple of things to explore.
Back in 2006 I got a contractor position to work for a large company. So, I gave my resignation at my current job and set things up that I would have one week off between jobs. During that one week, apparently the large company that I was supposed to be a contractor for decided that they no longer needed the extra resources and I am not needed. So, I was out of luck and out of a job.
Since I was already interviewing, my mind was prepped for the whole interview gauntlet. Interviewing full-time definitely helped out since it allowed a lot of time to study and prep. So, it took about another month to find my next role (full-time, not a contractor!).
I, personally, always send one; especially if I am considering taking the job even after the interview. I feel like it shows my interest in the company.
I am an engineer and have experience building data pipelines with Hadoop and a lot of the Hadoop ecosystem. I like data and solving problems with data. Python is my main go-to language as of late, but I am language agnostic and use whatever tool is right for the job.
I am looking for opportunities where I can work with more data.
Same here; though the guess was nine years older than I am! I am just going to assume that they don't have enough folks that look like me in their dataset.
I'm curious to hear more about the accuracy of their machine learning algorithm though. I'll need to read into that later.
There is definitely a need with documentation and even style guides and such. I've seen a bunch of pull requests that are merely just edits to grammar and such.
There are also projects like 500lines (https://github.com/aosabook/500lines) where it's a book and you can help out with all types of editorial-type tasks.