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Amazon data science interview questions

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Re: Amazon data science interview questions

#31

Post by chronic6h2 »

ju-st wrote: post #15
hackernewsacct wrote: post #4

If you obtained a degree in Computer Science and specialized in Machine Learning are you suppose to be able to answer these questions? What job specialization is this aimed for? Almost strikes me more as a statistical based interview.

I have the impression that at big universities maths is always the #1 topic in CS/ML. So its no surprise their graduates ask the same riddles as their profs.

As long as these riddles keep the web devs and infra engineers away from machine learning, I'm all for it.

We must preserve the elite reputation associated with machine learning; not watered down by avergae engineers looking for a career change.

Re: Amazon data science interview questions

#33

Post by cfusting »

hackernewsacct wrote: post #4

If you obtained a degree in Computer Science and specialized in Machine Learning are you suppose to be able to answer these questions? What job specialization is this aimed for? Almost strikes me more as a statistical based interview.

Statistics and machine learning have a huge amount of overlap. Almost seems silly we separate the fields.

Re: Amazon data science interview questions

#34

Post by autokad »

hackernewsacct wrote: post #4

If you obtained a degree in Computer Science and specialized in Machine Learning are you suppose to be able to answer these questions? What job specialization is this aimed for? Almost strikes me more as a statistical based interview.

a degree in computer science is really inefficient if you want to be a data scientist. imagine a 10 class CIS masters: with graduation restrictions you might be able to take 3 classes that directly relate to data science. good luck in your job interviews if you took them first, as you spent 20 hours a week on homework to fill requirements you will never use.

now take a statistics major, every class is relevant, and you can still take machine learning in your electives. win win.

I came to this conclusion after I noticed more of my classmates in the mba program (wharton) as data scientists than people in computer science who took machine learning. in fact, _all_ of the CIS majors in machine learning who really wanted to be a data scientist ended up as engineers.

so then I started doing a small search on linkedin, only looking at the big tech company data scientists. selection biases aside, out of 12 profiles: 5 statistics majors, 5 business, 1 biophysics, 1 IT major.

I have also done some looking into interview questions via glass door, and you get grilled on statistics questions. this matches my one interview with uber in 2016. I only got asked 2 ML questions: what is random about a random forest, and in KNN, what happens to bias & variance as K goes to 1

if you want to be a data scientist, you need to learn stats really well or getting past the interview process is going to be very difficult.

Re: Amazon data science interview questions

#35

Post by gaius »

rothbardrand wrote: post #7

It appears that the current generation of "hackers" seems very keen to work for a big name company-- Amazon, Apple, Microsoft, Google, Facebook. As someone who has worked for many startups and several of the above named companies, please let me give you a bit of advice: - A big company on your resume has no outside value to your prospects. Seriously. There's not "hey well he worked for amazon so we know he's good" fr…

Seriously. There's not "hey well he worked for amazon so we know he's good" free pass in the future for having Amazon on your resume.

The point of a CV is to get you an interview. A person who graduated from an Ivy/Russell, did a year or two at Google and a similar spell at Goldman Sachs, will be able to get an interview anywhere, for the rest of their lives.

They probably won't get an easier ride in the interview, it may even be harder as the interviewer's egos insist that they best one of the "elite", but they will never need to worry about passing a screen.

Re: Amazon data science interview questions

#36

Post by rafinha »

I have mixed feelings concerning this methodology. At the same time I feel I'm a bit rust on the details of the field, I still believe best way to assess academic background is by sending a paper "offline" and asking the interviewee to explain it. IMO all these quick-answer questions asses is how prepared is the interviewee in answering quick-answer questions.

Re: Amazon data science interview questions

#37

Post by gaius »

cfusting wrote: post #33
hackernewsacct wrote: post #4

If you obtained a degree in Computer Science and specialized in Machine Learning are you suppose to be able to answer these questions? What job specialization is this aimed for? Almost strikes me more as a statistical based interview.

Statistics and machine learning have a huge amount of overlap. Almost seems silly we separate the fields.

Well yes. Before the trendy buzzword, machine learning was known simply as predictive statistics.

Re: Amazon data science interview questions

#38

Post by gaius »

ju-st wrote: post #15
hackernewsacct wrote: post #4

If you obtained a degree in Computer Science and specialized in Machine Learning are you suppose to be able to answer these questions? What job specialization is this aimed for? Almost strikes me more as a statistical based interview.

I have the impression that at big universities maths is always the #1 topic in CS/ML. So its no surprise their graduates ask the same riddles as their profs.

CS is discrete maths, which is not quite the same as statistics.

Re: Amazon data science interview questions

#39

Post by stale2002 »

chronic6h2 wrote: post #31
ju-st wrote: post #15

Earlier quoted context omitted.

I have the impression that at big universities maths is always the #1 topic in CS/ML. So its no surprise their graduates ask the same riddles as their profs.

As long as these riddles keep the web devs and infra engineers away from machine learning, I'm all for it. We must preserve the elite reputation associated with machine learning; not watered down by avergae engineers looking for a career change.

People have been doing statistics for decades, which is mostly all that machine learning is. Coming up with a fancy new buzz word for stuff that has been for decades, doesn't make something "elite".

Re: Amazon data science interview questions

#40

Post by icelancer »

RA_Fisher wrote: post #24
prestonh wrote: post #5

Can't say I could answer all these questions, but I think they're really great and motivate me to spend more time studying statistics. With the rise in data science and machine learning I've noticed a lot of resources devoted to teaching people how to create and train models for a given problem, but less resources on how to interpret those models and on statistical inference in general.

It's quite rare to find folks in the industry with formal education in statistics. The folks that have it can run circles around everyone else, though. Data Science and Analytics and Machine Learning all use statistical theory when boiled down.

When I ran a Data Science team we primarily hired Physicists and Mathematics majors and not CS graduates for this reason. It mostly worked as intended (untapped source of excellent candidates), but some of them could not for the life of them pick up software development / writing manageable code with a team. They were so used to writing unmanageable scripts that didn't have long-term time horizons (think: horrors of hundreds and thousands of lines of R-stats code in a single file, uncommented, and brutal to look at, with the expectation we'll just plug it into R-script on the command line) that occasionally this became a very tough habit to break.

Still, besides that issue - which all novice programmers have, but Data Scientists come in at a much more senior level - it was a great market advantage, one that I think is largely gone today, as companies understand the need for statisticians and economists who really and truly understand modeling and math.

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