A few months back I wrote about my experiences trying to hire a data scientist. It took some amount of work on our part. When we finally found the right candidate, our parent company told us that there wasn't actually any money to pay a candidate. This came as rather a surprise to all of us at our three person startup. This was the first indication that the wheels were coming off the bus, and two months later, we were all laid off and the company dissolved. Within just three months I went from hiring to scrambling for a job. Would I follow my own advice for job candidates? What's the startup climate like? Is it easy to find a job in the field?
getting a foot in the door
I decided to make of habit of (nearly) always writing a cover letter, although I quickly settled on two or three templates of cover letter, depending on the job function and industry. I found the address of each company and included it in the letter, mostly to confirm that the office was in the city of San Francisco. When I submitted an application, I would save the letter in my (private) applications repo on github, with a message. I had been warned by a friend who works in HR that cover letters were ignored in her office. In my experience, a cover letter, even a somewhat generic one, set apart casual applicants from the serious candidates.
I also made the not uncontroversial decision to send out my lengthy CV, rather than a one or two page resume. My thinking here was that it is easier for a hiring manager to read more details in your CV if they are interested than try to infer details from a terse one page resume. Towards this end, I tried to include, for example, a one or two sentence summary of the packages I have on CRAN. This seemed better than just including the package name and a link. I did get scolded by interviewer for having a too-long CV (militant environmentalist? staunch foe of self-aggrandization?), so maybe this is not the right way to go. It would be an interesting experiment to post the same resume at different times but in 1 and 2 page versions to a job board, to see if recruiter response is sensitive to page bloat.
I have heard and read that jobs are 'typically' found by networking. I am not a naturally schmoozy person, and my own experience has been mixed: I actually found employment twice at quantitative hedge funds on craigslist, which is probably a world record. I did some first- and second-degree networking, and almost landed an offer through these channels, but I also put in a lot of leg work on the internet combing through job boards. Part of my justification is that I could search through dozens, maybe hundreds of job postings in a given evening, whereas the human-interaction route, even if higher yield, had lower bandwidth.
I started with a bunch of job site RSS feeds from my last job search, years ago. These were still active in my digg reader account, and I just picked up where I left them. These have a lot of duplicates, are often not geographically appropriate, and have a high type II rate because I have not maintained them. There were only a few new interesting posts a day, and maybe I applied to two or three a week I got through this route.
I felt I needed to increase my apply rate to 5 applications per day. So I branched out to the Muse, angel list and LinkedIn's job search page. These each are weird in their own ways. The Muse includes an image of the office where you would work, but had pretty poor geographic locality. (Because I hate commuting, I was not going to consider anything outside the city of San Francisco.) Angel posts salary and equity ranges and is heavy on the startup hype. LinkedIn. Well.
LinkedIn. I was told that some companies would only post paid ads on LinkedIn. In my snooping I did find a number of postings which I saw nowhere else. LinkedIn's geographic capabilities were pretty poor however, only allowing one to pinpoint a job to within 5 miles from a given zip code. For my case, this meant some jobs from Oakland, San Mateo, and so on slipping in. I also found that LinkedIn appeared to import job postings from other sites, often translating 'San Francisco Bay Area' (i.e. Palo Alto or something) to 'San Francisco'. LinkedIn appears to implement some small amount of 'machine learning' in their job search functionality, with hilarious results. My search for 'mathematician' in my zip code yielded results for 'Pizza Hut Delivery Driver', 'Cake Decorator at Whole Foods', and 'Waitress, Hustler Club'. Apparently 'mathematician' shares a stem with 'math', as in "basic math skills," and so you get these terrible results. I should note this is the strict search functionality, not the 'suggested jobs' functionality. Nevertheless, given how much LinkedIn knows about me (sharing more information with them was necessary to speed up my application process for various jobs), it is utterly bizarre that such bad hits were surfaced. Or perhaps suggesting that the former (assistant) math professor go get a job as a pizza delivery guy is a snide joke.
I used LinkedIn's job search notifications for a while. I was amused to find that a search for the 'data' keyword would result in emails titled, "1000 new jobs for 'data' in San Francisco". Not all of them were for pizza logistics, but combing through 1000's of jobs a day was too much for me.
After 'graduating' from LinkedIn, I spent a good twenty minutes using Glassdoor's job search before giving up. I am sure it is just fine if you like clicking around a lot, but the user interface was terrible, even if their geographic locality was better than LinkedIn.
I then wandered into indeed. Indeed has decent geographic locality, tons of job postings, and a fine user interface. After applying for a few jobs through the site, I was encouraged to post my resume there. The next day I had half a dozen emails and three calls from recruiters, who apparently watch the new resume feed. Over the years, I have had maybe zero good results from talking with recruiters, and was pretty skeptical. Quite a few wanted to share with me jobs that I had already found (and in some cases applied for) through my search process. Perhaps using a recruiter gets you to the head of the line, but I have some doubts.
the interview process
Years back, when I was fresh out of school, it seemed that interviews, at least for the 'quantitative gun-slinger' variety, always consisted of a bunch of brain-tweezers. Charitably, I will speculate now that these were common because I did not have a lot of experience. I will go out on a limb and state that this is a terrible way to interview candidates (although perhaps not much worse than every other interview tactic). First, think of the power dynamics here: the interviewer knows the answer to a question, one that they themselves may not have figured out, yet they keep mum and watch the interviewee twist in the wind. What will it be like to work with that person? Will they withhold key information to see if you can figure it out yourself? Will working at the job always make you feel dumb? Is your job an endless series of brain tweezers? Is this the best we can do?
When I was interviewing, I was fairly certain that the 'homework problem' was a much better screen: closer to what the actual work would be like, you learn a lot about how a person thinks and works, and you might get some free consulting out of them if the problem is actually of interest (and it should be). And then I found myself in the position of having to submit a whole bunch of these during my flurry of interviews, typically before I knew enough about the company to determine whether I should proceed. My suggestion with these, and I stuck to this line, is to set a strict time limit of one or two hours. Make sure you have enough time when the HR contact sends it to you, and complete it within this short time limit, and return it, refusing any offer to "take more time." Make sure they know how valuable your time is.