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Lessons from 3,000 technical interviews

blog.interviewing.io

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Re: Lessons from 3,000 technical interviews

#111

Post by davedx »

collyw wrote: post #2

Interesting and surprising, especially the experience thing. I think I am a significantly better engineer than earlier in my career, so I assumed experience would count for a fair bit. Then again I have inherited projects from experienced guys who make crap high level architecture decisions and the code is way more difficult to work with than it ought to be. But then this article seems to be measuring interview perfo…

I am conducting interviews at the moment. I would say experience gives you a much better chance of getting to interview but once you are there other factors can be more important, like motivation and communication abilities.

Re: Lessons from 3,000 technical interviews

#112

Post by geebee »

sporkenfang wrote: post #37
geebee wrote: post #14

Interesting bit on the MS degree. I followed the link, and I'm not quite as surprised that the correlation is poor, or even negative, given the way the data was collected and analyzed. Absolutely agree that some MS degrees are pretty much less rigorous cash cows by now, that allow students to skip the fundamentals such as data structures, operating systems, and compilers. However, many CS MS degrees actually do requi…

I'm curious what would happen if they looked at, as separate categories, people who mastered out of a doctoral program, people who did the 5-year BS/MS, and people who obtained a doctoral degree as well as a master's.

That could be useful. The article mentioned rhat there was no distinction made between CS masters degrees and Info Systems degrees.

My guess is that pure MS would correlate positively from CS programs that require a background in more advanced math and algorithms. Info sys degrees typically don't.

I'm not knocking those degrees, keep in mind we're measuring performance on a technical interview, which often leans very heavily toward algorithms, trees, sometimes graphs, and occasionally numerical analysis or computing.

If the MS degree data includes a lot of programs that dont include this background, then this woukd not be a surprising result.

Re: Lessons from 3,000 technical interviews

#113

Post by phd514 »

k2xl wrote: post #83

Interviewing is a funny thing. I remember when I graduated from a "Top School" and interviewed at "hot startups" from the valley. I aced a lot of the interviews - why? Because I had just taken classes on LinkedLists, Binary Trees, HashMaps, etc... So when they asked me to whiteboard a "shortest path algorithm" it was just rehashing what I did in school. Years later, looking back, I fail to see the relevance in most o…

That has been my experience, too. I remember deriving the optimal solution for an interview question that was a variant of a radix sort and impressing the interviewer for one of the hot startups at the time. That was partly the result of my ability to recognize the similarities between the problems but even more a consequence of having recently studied radix sorts. Twenty years later, I'm a much better developer than I was then and have shipped many projects with significant degrees of complexity, but I couldn't answer that interview question or ones like it as well today as I did then.

Re: Lessons from 3,000 technical interviews

#114

Post by wikibob »

dibstern wrote: post #105
forrestbrazeal wrote: post #71

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…

Which program are you doing?

Re: Lessons from 3,000 technical interviews

#115

Post by grigjd3 »

collyw wrote: post #2

Interesting and surprising, especially the experience thing. I think I am a significantly better engineer than earlier in my career, so I assumed experience would count for a fair bit. Then again I have inherited projects from experienced guys who make crap high level architecture decisions and the code is way more difficult to work with than it ought to be. But then this article seems to be measuring interview perfo…

If someone works at a firm with bad processes / poor or no code review, this can actually make their experience a detriment as they continue to use and reinforce bad habits.

Re: Lessons from 3,000 technical interviews

#116

Post by [deleted] »

jonathanfoster wrote: post #103
forrestbrazeal wrote: post #71

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...

[deleted]

Re: Lessons from 3,000 technical interviews

#117

Post by ortekk »

dibstern wrote: post #105
forrestbrazeal wrote: post #71

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…

Could you please elaborate? It looks like this program is only for people that already have an CS-related degree.

What courses are you taking?

Re: Lessons from 3,000 technical interviews

#118

Post by closed »

Interesting article! Some minor statistical pet peeves:

1. Setting non-significant bars to 0 seems fishy. Leaving them and putting confidence intervals on everything would let them speak for themselves.

2. Calling something effect size is ambiguous. That's like saying you measured distance in units (and the wiki article on effect size linked makes clear there are a billion measures of effect size).

I'm guessing their measure of effect size were the beta coefficients in a multiple regression?

Re: Lessons from 3,000 technical interviews

#119

Post by janeandrews »

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Re: Lessons from 3,000 technical interviews

#120

Post by jghn »

ma2rten wrote: 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…

I think the point here are folks taking MOOCs for enrichment, not as a gateway to get a job. So for instance someone taking the ML course just for knowledge, not to try to get in the door as a data scientist
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