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Lessons from 3,000 technical interviews

blog.interviewing.io

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Re: Lessons from 3,000 technical interviews

#201
post #92

Until recently I worked at a startup as Machine Learning Engineer/Data Scientist. There I got some experience interviewing people and looking at their resumes. In my experience, which is very limited compared to this post, people who put an MOOC on their resume are usually less qualified compared to people who don't. There is nothing wrong with MOOCs, but they are almost always beginner-level. If you put them on your…

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Re: Lessons from 3,000 technical interviews

#202

Earlier quoted context omitted.

Made a similar comment above, but that was entirely true for myself. I have worked on amazing things as we all have in life, petabyte databases, and just the most incredible setups. But when it comes to an interview, I cannot get a job several levels below my own (without referrals). With referrals, I am offered the moon and the stars, complete pick out of a tremendous number of amazing jobs. But any random interview…

You cannot get a job at a top company without referral/recruiter looking you up. Any such company is totally swamped by the number of resumes submitted and the chance of getting an interview is practically zero.

This is not even close to being true. People get hired into top companies all the time.

Re: Lessons from 3,000 technical interviews

#203
I think you are seeing the effect of people who have decided for themselves to pursue lifelong learning. The Udacity/Coursera thing just clusters these people in a way that you notice them in the stats. But remember that statistics do lie. You need to dig into the reality behind the numbers, and question whether you are measuring all the right indicators.

My experience comes from several decades developing software and from time to time, hiring people. The people that worked out best, either as colleagues or hires, always seemed to be learning new things and were ahead of the curve trying out new techniques or tools before they became popular.

If you understand how a tool/technique becomes popular as the mass of software developers wrestle with new problems and finally find a way to master them, then it makes sense that constant learning makes some people stand out of the crowd. They happen to be the first ones to learn the new tool/technique and if they do not introduce it to their development team, then when management does make the decision to introduce it, the folks who know how to drive it have a chance to excel and appear to be rocket scientists.

Re: Lessons from 3,000 technical interviews

#204

The author draws a hard distinction between Udacity/Coursera MOOCs (good) and traditional master's degrees (bad). I'll interject that with Georgia Tech's Online Master's in Computer Science program [0], which is delivered via Udacity and insanely cheap [1], you can get the best of both! (Their "Computability, Complexity and Algorithms" class is one of the top Udacity courses cited in the article.) Keep in mind that a…

$6,600 [1] for a master's from a top 10 computer science program [2] is an absolute steal! My master's program costs that per semester. [1] https://www.omscs.gatech.edu/prospective-students/faq [2] http://grad-schools.usnews.rankingsandreviews.com/best-gradu...

You live in the wrong country.

Re: Lessons from 3,000 technical interviews

#205
post #157

Earlier quoted context omitted.

"Intellectual curiosity" was my primary attribute for many years. Particularly when I was young and didn't really know any better. It makes sense doesn't it? Someone who is interested in learning for learning's sake will be a better developer! Except I'm convinced it's not really true. It's something that is horribly subjective and really self-selective. It's funny, intellectually curious people often have exactly th…

You had me until, "it's a really good signal when they pull out their phone and add it to a to-do list." Because it's just one of many possible courses of action for staying organized. For all you know the guy added it to his to-do list on his way to the car, or maybe he employs some other mechanic. While you could argue that an interview is a showboating environment where one is expected to signal certain desireable…

It's a signal. It's not a binary yes/no, there are many observations we're making throughout the interview. This is just one, and the to-do list isn't the only correct answer. Asking me to email those details to them is another possible right answer. Writing a note in a notebook is fine.

The key thing to remember here is that we're asking this very much in the middle of the interview, and I just want to see that they have some sort of system in place for remembering these things.

In my experience, most of the time, simply going "sure, I'll do that" and depending on memory to actually get it done is a negative signal. Maybe they are particularly gifted in terms of memory, but in my experience that is rarely the case.

In hiring we're willing to accept false-negatives, but never false-positives. You are correct, I may let a perfectly good candidate walk, but I'm willing to accept that as the cost of hiring a bad one is just too high.

Re: Lessons from 3,000 technical interviews

#206

"Whether passing an algorithmic technical phone screen means you’re a great engineer is another matter entirely and hopefully the subject of a future post." This sentence plus the inverse correlation between experience and "interview performance" shown there. Makes a big smell about how biased are those interviews to themselves and not to real technical interviews. From the data it looks like the questions asked usin…

Yes, because we all know that your ability to implement a red-black tree from memory has a direct correlation with your ability to implement some random business logic or CRUD app. Oh wait, they don't.

I used to think along these lines. Then I started doing 10+ interviews a month and realized a very clear reality: basic CS knowledge and problem skills is far more important to me and my team then knowing how to slap together some semblance of a working CRUD system.

I ask "algorithmic" questions, normally expressed as a legitimate business case (invent a real world problem, solution is implement some algorithm or use specific data structure). My warm up question typically is a simplistic "find the subset in a given collection that matches this specific criteria" (with a subtle implication of "do it efficiently"). The average coder should be able to solve this type of thing, on their own, in about 10 minutes max, 15 with some feedback on improvements.

Yet, 80% of my candidates take nearly 45 minutes and cannot deliver a workable solution without massive handholding, and I don't even get to my higher order, "real questions". The scenario of a coder who can't solve my warm-up being let loose on code I actively maintain makes my stomach churn.

Until I see the average bar for problem solving go up, I'm going to keep asking basic CS questions in my coding interviews. The job is to solve complex, typically ambiguous problems. Coding is one of the tools - and I want peers who understand the theory behind using those tools.

(I should note, I tend not to pay attention to credentials on a resume. I care more about ability to do the job then past history - though if a candidate has a masters in some field of CS, I might delve into it a bit out of curiosity... they are an expert afterall)

Re: Lessons from 3,000 technical interviews

#207
On the master's front, I went down a slightly unusual path. I enrolled in a master's program in music technology at NYU [1]. I already had a master's in engineering from Princeton [2], but after time away from the software world, I wanted to retool for a return to engineering, but with a focus on applications that actually mattered to me.

It turned out to be a very expensive, but very fulfilling decision, and it paved a route for a very successful past four years.

Compared to my first master's, it was less theoretical and much more project-based. In that sense, it was fantastic preparation for career work, because every semester, I had to conceptualize and ship 4-5 different projects in all sorts of subject areas. The value of that shouldn't be underestimated. It also directly led me to cofounding a startup that had a brief lifetime, but effectively converted me to a full-stack engineer.

Today, I don't use much of the subject matter I learned in my day-to-day, but I draw on the creativity, problem-solving skills, and work patterns every day.

My Princeton program was great too, but I thought I'd share about the NYU program, as that was the more outside-the-box choice. There's something special to be said for a master's degree, when it's interdisciplinary and let's you focus on the intersection of engineering skills and subject matter expertise.

[1] http://steinhardt.nyu.edu/music/technology

[2] http://ee.princeton.edu/graduate/meng-program

Re: Lessons from 3,000 technical interviews

#208

The author draws a hard distinction between Udacity/Coursera MOOCs (good) and traditional master's degrees (bad). I'll interject that with Georgia Tech's Online Master's in Computer Science program [0], which is delivered via Udacity and insanely cheap [1], you can get the best of both! (Their "Computability, Complexity and Algorithms" class is one of the top Udacity courses cited in the article.) Keep in mind that a…

I'm studying a 3 year coursework masters that allows people with no background in CS (just had to do an additional semester of courses) to participate and it aims to give a pretty well rounded CS education. Not a common thing, apparently. I completely agree, the motivation and environment that it gives you, the reinforcement that you're actually doing something official and serious as opposed to doing something that…

I am curious what program you are taking as well.

Re: Lessons from 3,000 technical interviews

#209

The takeaway from this is that those who do best are those with: - the wealthiest/most financially supportive parents/relatives - upbringings that are conducive to academic success - the most free time as those are the ones who, by a large margin, attend top schools, work at top companies, and have time to spend on self-learning. Another data point of confirmation of a well-studied idea. Assortative mating: http://ww…

Hypothetical question: If I could show that people who complete Coursera/Udacity courses tend to be poorer than average, would that be a "data point of disconfirmation of a well-studied idea"?

Re: Lessons from 3,000 technical interviews

#210

The author draws a hard distinction between Udacity/Coursera MOOCs (good) and traditional master's degrees (bad). I'll interject that with Georgia Tech's Online Master's in Computer Science program [0], which is delivered via Udacity and insanely cheap [1], you can get the best of both! (Their "Computability, Complexity and Algorithms" class is one of the top Udacity courses cited in the article.) Keep in mind that a…

$6,600 [1] for a master's from a top 10 computer science program [2] is an absolute steal! My master's program costs that per semester. [1] https://www.omscs.gatech.edu/prospective-students/faq [2] http://grad-schools.usnews.rankingsandreviews.com/best-gradu...

These numbers still look very high from a European point of view. It seems it makes a huge difference whether a society deeply cares about educating the population, or cares just superficially.

For example, in Berlin you spend less than 300€ per semester, a CS master takes 10 semesters regular time. Add two semesters to make the time more realistic, and you end up with 3,600€ which are roughly $3,800.

Oh, and it contains a full time ticket for public transport (which would otherwise cost 970€/year, i.e. 485€/semester). In other words: University education is cheaper than regular public transport, even though it contains a full time ticket.

Oh, and if your parents don't have that money, you can get half of the university costs + half of the living costs + half of the rental costs from the state. [1]

And note that Germany is by far not the best one in Europe regarding education, in universities as well as all other types of schools. It is regularily and heavily criticized for cutting educational expenses more than is good for the country. [2] However, after reading statements like the parent comment, I suspect it is still pretty good.

[1] More precisely, you get a debt called "BAföG", from which you have to pay back only ~50% after finishing - either in rates or all at once.

[2] For example, this forces universities into projects financed by third parties (i.e. companies), which adds a strong bias to the research direction and even more so to the results. Even worse, if this research contains business internals (which is easy to claim by any company), this leads to results being only partly published, or not being published at all. To be fair, the latter is more a problem of the law and not of third-party project. There should be a law that demands everything that is fully or partly paid with public money is Open Access as well as Open Source.

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