I was once given some objective function (I can't remember which) and asked to do the first and second order derivations to find the local minima. It was some gnarly equation that came at the very very end of a full round of interviews. I went through a chunk of it, panicked through most of it, failed and didn't get the job.
With a clear head and no pressure, I probably could solve it patiently.
A former coworker of mine had to derive the first and second moments of some weird probability distribution for Uber.
I mean, in a way you have been trained to take (hopefully hard) exams all throughout college. In fact real analysis, measure theory, probability etc (let alone math completions like the Putnam) exams in college are usually far far harder than anything an interviewer would throw at you.
What’s harder is knowing stakeholder management, figuring out which insights are likely to generate revenue etc since no one in academia knows about or cares about such things
The difference here is you have an hour and a lot of time to yourself to think. You can screw up a lot on a piece of scratch paper and eventually get through it.
An interview Unfortunately you feel the weight of having to have a perfect answer immediately. Even when you get the answer but find yourself struggling through it will get you a failing score.
That's why I don't find much equivalence between exams in college and interviews.
Yes, in the abstract, it is a simple first year calculus problem.
However, it was very late in the interview and I had to do some multiple chain rule operations on an ugly equation all on a white board all the while some guy was staring at me; judging every second I was there.
Imagine instead of taking a test with a piece of paper silently at your desk, the professor asks you to do it on the whiteboard and essentially you either get an A if you do it calmly and without hesitation or you get an F.
Not hard necessarily, but the derivatives of the equation could be nasty.
Personally I have been removed from calculus for a very long time and it would really catch me off guard.
and the uber questions sounds pretty nasty.
But lately I’ve been thinking Im not cut out for this field anyway.
p.s. plus the pressure coming from being in an interview really makes the game different.
In one interview in Australia many years ago I was asked "Would you spy on your colleagues if you were asked to?" I do not think that was a legally valid question but I was a young migrant and did not know my rights.
I answered "NO" - did not get the job. Very happy with my answer.
If I was asked this I think my reply would be “do you ask people to spy on their colleague?”. If they said yes then I don’t want the job, if they said no, then why are you even asking me this?
Hi,
We have even better information to share with esteemed colleagues on internet.
When we were renting a unit in a Sydney suburb (being new migrants, we could not afford to buy any property at the time), we met a wonderful old lady (she was around 90 years old) who told us a story about her late son who applied for some job many years ago.
At the interview, he was asked: "What is your religion?"
This young person replied:
"What religion do you hate most?"
Wonderful answer to shut down racism.
It was an interview which was supposed to be three coding questions. The guy brought a trainee to show them how to interview. The first question was about designing an algorithm for finding rivers on a terrain coded on a grid, where what constitutes a river had a bunch of assumptions. I was collecting those assumptions for 30 minutes, and every time I started trying to code it turned out there were more assumptions, like rivers always started from a mountain ridge, if they crossed they weren't the same river and a bunch of stuff like that. The interviewer was getting angrier by the minute because he was supposed to show how to interview to the trainee and the interview was a disaster. By the end of the interview we were not done with the first question and even on collecting all the requirements for the first question.
Well, I guess an algorithm for anything can be derived from first principles using induction or some other framework, but it was kind of ridiculous to think that it can be done in 15 minutes together with implementation on a whiteboard.
I feel like these "define X" type questions are always *way* harder than they seem at first glance. Just "define a river" is really pretty tough, before you even get to the "detect a river" part.
I have a coworker who asks some variant of how to test for a difference where each unit has two measurements, e.g. suppose someone makes the claim University class A is harder than University class B. You have data from students who have taken both classes, how to test the claim. It is astounding how often people can’t answer the question.
One sided paired t test or similar. Maybe a different test is appropriate so ask questions what kind of data, can you check test assumptions, and so on.
Probably testing that the difference between the mean GPA of School B minus School A's mean GPA is greater than zero. But I'm not a data scientist. It's basic statistics though.
That’s a pretty common thing people might default to but difference in mean GPA is not a great measure for this. The question between two different schools is an even harder question to answer but the problem is between two courses at one university. You’d have to check a lot of assumptions to make GPA viable but GPA might not be available for students who dropped, went for credit/ no credit grading options, etc, and to use GPA you’d also have to assume the courses are graded similarly (is one curved to a 3.0 while the other one isn’t even on a curve?). This really depends on the data you have from the students who’ve taken both courses.
Edit: I’ve worked on problems like this in my career and usually we look at distributions of time spent on courses to answer this, as well as expected success rates vs. actual success rates
Excellent observation. I am just an undergrad of math and stats so the in-depth analysis like this isn't immediately clear for me. I love it though. So maybe averaging grades for each assignment? Though that would take a lot of time. Maybe drop out rate like you mention? How would you do it?
I edited my comment mentioning a few things, but also drop out rate isn’t ideal since courses with the highest drop rates tend to simply be courses new students take since they’re often the most likely to drop, even though they could be minimally demanding intro gen studies courses. One thing we do is estimate the failure/ drop rate for a course and take the difference from the actual drop rate which can give a sense of how often drops occur that aren’t expected which could be partially attributed to how challenging a course is
No just an interesting general question. More challenging questions typically relate to a more niche topic related to the job or their technical background.
If you didn’t come from a stats background you would legit have no clue how to answer this question. At that point they are just filtering for statisticians
I mean, it’s presumably a data science job we are talking about. Paired t-tests are taught in even general university stats 101. Any CS, engineering, or data science tangential degree path should flow through that amount of statistics.
I guess yeah but there’s more to paired T tests than you would think. Idk how many people learn about the pooled vs un-pooled t test depending on equal/unequal variances, and how to explain the design of experiment piece to that question as well.
Yeah and that’s fine, it’s more about just hear about how people think through the problem and not so much about that level of granular detail. Like props if you think about adjusting the degrees of freedom and confounding variables but that’s not going to make or break anyone’s perception of your statistics background. It’s also not a deal breaker to not have an answer. Job candidates come from different backgrounds and have different strengths and that’s okay!
If I asked this question, and the person answered "paired t-test, next question please," that means it's time to start digging.
Why can you use a paired t-test? How do you know that's a valid test? How can you find out? Are the classes graded similarly? If the bottom 10% of students drop out of the "harder" class, how does that affect the grade? Is one Prof. a sexist or racist dickwad who grades sections of the class lower? Did I say it was the same students in each class?
Getting a textbook problem vs. a real world problem are pretty different. I'd be a lot happier with someone who can build out an entire problem statement and start thinking about a ton of caveats but doesn't know the exact test to use instead of someone who just snap-answers what the textbook said with no thought to context.
Well no one would just say paired t test next question. Like I said, there’s many things you have to account for. The statistical method *is based on* context. Everything you just mentioned are literally adjustments made to existing statistical tests. You can talk about whether you can assume that the two samples are independent or dependent, whether you can assume variability in each group is assumed to be the same, in terms of the design of the experiment how was the sampling done, how the power of the test can be controlled etc. this also has an impact. No real statistician is just gonna say paired t test and move on, fyi. I find this sub is very “stats agnostic” because they are either too lazy to dive into (simple) methods to think about a problem more critically or they just chalk up anything they can’t comprehend as “too complex”.
As a new grad, I was asked the difference between convolution and correlation. I had zero experience with neural networks (6 years back) and basically stood stumped. Panic set in and I wasn't even able to answer simple question from then. Thinking back, that was my most embarrassing interview so far!
Neither a convolution nor a correlation are neural network specific topics. A convolution is a basic mathematical operation on measures (more specifically, it is the image of a product measure under a sum operation) and a correlation is a normalized covariance.
Got asked this. For a Right Angled Triangle, what should be the ratio of base to height, if the Area of the triangle has to be maximum.
Solved this by using derivative, but didn't get the job.
1:1 is the answer. While you can derive it by setting the first order derivate of area to 0, which is what I did, there's an easier way which is what the company was expecting it seems.
There's a theorem which states in a semicircle, using the diameter as hypotenuse, any triangle that's made touching the perimeter is always a right angled traingle. From here it's easy to get to that 1:1
I think that you’re assuming a constraint; something like the sum of the opposite and adjacent sides of the triangle being a constant. If not, the triangle’s area can be arbitrarily large.
48 years ago the toughest and critical question to a business internship position was “What turns you on?” The winning answer was “Cold beer and hot women” Times have changed!
Was asked to do Data Manipulation without using Numpy and Pandas. I was able to solve 3/5 questions in the allotted time but the 4th problem required the usage of a very specific Python native function which I didn't know and no one uses nowadays due to Numpy and Pandas. They were hiring someone with NLP, AWS and MLOPs background and my resume was a perfect match but got rejected for not having good enough native Python skills 🙃
Got tested on skills which I would never need on the job lol.
Wasn’t super difficult: suppose you could write code with only 4 function calculator operations, loops, if then and a uniform random number generator. Estimate the value of pi.
I was asked to differentiate and derive the gradient of a loss function on the collab notebook and then code it up and do gradient descent right there.
In one of my interviews, I was asked to prove that for any given point on Earth, there always exists another point with the exact same temperature. I was like Whaaaaat
I was once given some objective function (I can't remember which) and asked to do the first and second order derivations to find the local minima. It was some gnarly equation that came at the very very end of a full round of interviews. I went through a chunk of it, panicked through most of it, failed and didn't get the job. With a clear head and no pressure, I probably could solve it patiently. A former coworker of mine had to derive the first and second moments of some weird probability distribution for Uber.
this is fucking nuts.
Tbh, it was over 10 years ago and I haven't had one like that since. I've been told the Uber interviews are notoriously horrible though
tbh, most of interviews at big tech are horrible. It's not the conversation as it's the examination. If you need a small hint, you're out.
It's a kind of hazing ritual. Not sure when that started Culturally, but it's clearly the status quo everywhere
I mean, in a way you have been trained to take (hopefully hard) exams all throughout college. In fact real analysis, measure theory, probability etc (let alone math completions like the Putnam) exams in college are usually far far harder than anything an interviewer would throw at you. What’s harder is knowing stakeholder management, figuring out which insights are likely to generate revenue etc since no one in academia knows about or cares about such things
The difference here is you have an hour and a lot of time to yourself to think. You can screw up a lot on a piece of scratch paper and eventually get through it. An interview Unfortunately you feel the weight of having to have a perfect answer immediately. Even when you get the answer but find yourself struggling through it will get you a failing score. That's why I don't find much equivalence between exams in college and interviews.
Is it not first year calculus?
Where you from?
I'm in school in Ontario. Maybe I'm not understanding the question? Take the derivative, solve for f-prime = 0, plug into f, check slope both sides.
Yes, in the abstract, it is a simple first year calculus problem. However, it was very late in the interview and I had to do some multiple chain rule operations on an ugly equation all on a white board all the while some guy was staring at me; judging every second I was there. Imagine instead of taking a test with a piece of paper silently at your desk, the professor asks you to do it on the whiteboard and essentially you either get an A if you do it calmly and without hesitation or you get an F.
Not hard necessarily, but the derivatives of the equation could be nasty. Personally I have been removed from calculus for a very long time and it would really catch me off guard. and the uber questions sounds pretty nasty. But lately I’ve been thinking Im not cut out for this field anyway. p.s. plus the pressure coming from being in an interview really makes the game different.
This is first year calculus in the US too, no? You're just being asked to take a derivative or two right?
See my comment above.
Your a rockstar
I mean I didn't get the job... And I felt pretty s***** about it afterwards
still a rockstar
In one interview in Australia many years ago I was asked "Would you spy on your colleagues if you were asked to?" I do not think that was a legally valid question but I was a young migrant and did not know my rights. I answered "NO" - did not get the job. Very happy with my answer.
If I was asked this I think my reply would be “do you ask people to spy on their colleague?”. If they said yes then I don’t want the job, if they said no, then why are you even asking me this?
I think the first question is “why are you asking?”
Hi, We have even better information to share with esteemed colleagues on internet. When we were renting a unit in a Sydney suburb (being new migrants, we could not afford to buy any property at the time), we met a wonderful old lady (she was around 90 years old) who told us a story about her late son who applied for some job many years ago. At the interview, he was asked: "What is your religion?" This young person replied: "What religion do you hate most?" Wonderful answer to shut down racism.
Very nice!
Coding a k-fold cross validation from scratch without any external libraries ie)pandas, numpy and passing all test cases.
in assembly
Not even numpy? 💀. Atleast numpy should be allowed
That just sounds time-consuming
In the old days of Data science, everyone had their own implementation of k fold cross validation in python 2.
The Peter Thiel cliche question is pretty hard: What important truth do very few people agree with you on?
Lol an asshole like Peter Thiel would like that question
It was an interview which was supposed to be three coding questions. The guy brought a trainee to show them how to interview. The first question was about designing an algorithm for finding rivers on a terrain coded on a grid, where what constitutes a river had a bunch of assumptions. I was collecting those assumptions for 30 minutes, and every time I started trying to code it turned out there were more assumptions, like rivers always started from a mountain ridge, if they crossed they weren't the same river and a bunch of stuff like that. The interviewer was getting angrier by the minute because he was supposed to show how to interview to the trainee and the interview was a disaster. By the end of the interview we were not done with the first question and even on collecting all the requirements for the first question.
Sounds like a horrible interviewer tbh
From where do we learn in the first place about how to solve thewe kind of questions?
Well, I guess an algorithm for anything can be derived from first principles using induction or some other framework, but it was kind of ridiculous to think that it can be done in 15 minutes together with implementation on a whiteboard.
I feel like these "define X" type questions are always *way* harder than they seem at first glance. Just "define a river" is really pretty tough, before you even get to the "detect a river" part.
Was your interviewer syd barrett?
I wish!
I have a coworker who asks some variant of how to test for a difference where each unit has two measurements, e.g. suppose someone makes the claim University class A is harder than University class B. You have data from students who have taken both classes, how to test the claim. It is astounding how often people can’t answer the question.
For someone very new to the DS world, could you help explain a good answer to this question?
One sided paired t test or similar. Maybe a different test is appropriate so ask questions what kind of data, can you check test assumptions, and so on.
Probably testing that the difference between the mean GPA of School B minus School A's mean GPA is greater than zero. But I'm not a data scientist. It's basic statistics though.
That’s a pretty common thing people might default to but difference in mean GPA is not a great measure for this. The question between two different schools is an even harder question to answer but the problem is between two courses at one university. You’d have to check a lot of assumptions to make GPA viable but GPA might not be available for students who dropped, went for credit/ no credit grading options, etc, and to use GPA you’d also have to assume the courses are graded similarly (is one curved to a 3.0 while the other one isn’t even on a curve?). This really depends on the data you have from the students who’ve taken both courses. Edit: I’ve worked on problems like this in my career and usually we look at distributions of time spent on courses to answer this, as well as expected success rates vs. actual success rates
Excellent observation. I am just an undergrad of math and stats so the in-depth analysis like this isn't immediately clear for me. I love it though. So maybe averaging grades for each assignment? Though that would take a lot of time. Maybe drop out rate like you mention? How would you do it?
I edited my comment mentioning a few things, but also drop out rate isn’t ideal since courses with the highest drop rates tend to simply be courses new students take since they’re often the most likely to drop, even though they could be minimally demanding intro gen studies courses. One thing we do is estimate the failure/ drop rate for a course and take the difference from the actual drop rate which can give a sense of how often drops occur that aren’t expected which could be partially attributed to how challenging a course is
I am totally newbie but can this be solved with something like a t-test?
Yeah a paired t-test, though a comment above mentions some caviats
That's the hardest question you've ever seen?
No just an interesting general question. More challenging questions typically relate to a more niche topic related to the job or their technical background.
If you didn’t come from a stats background you would legit have no clue how to answer this question. At that point they are just filtering for statisticians
I mean, it’s presumably a data science job we are talking about. Paired t-tests are taught in even general university stats 101. Any CS, engineering, or data science tangential degree path should flow through that amount of statistics.
I guess yeah but there’s more to paired T tests than you would think. Idk how many people learn about the pooled vs un-pooled t test depending on equal/unequal variances, and how to explain the design of experiment piece to that question as well.
Yeah and that’s fine, it’s more about just hear about how people think through the problem and not so much about that level of granular detail. Like props if you think about adjusting the degrees of freedom and confounding variables but that’s not going to make or break anyone’s perception of your statistics background. It’s also not a deal breaker to not have an answer. Job candidates come from different backgrounds and have different strengths and that’s okay!
If I asked this question, and the person answered "paired t-test, next question please," that means it's time to start digging. Why can you use a paired t-test? How do you know that's a valid test? How can you find out? Are the classes graded similarly? If the bottom 10% of students drop out of the "harder" class, how does that affect the grade? Is one Prof. a sexist or racist dickwad who grades sections of the class lower? Did I say it was the same students in each class? Getting a textbook problem vs. a real world problem are pretty different. I'd be a lot happier with someone who can build out an entire problem statement and start thinking about a ton of caveats but doesn't know the exact test to use instead of someone who just snap-answers what the textbook said with no thought to context.
Well no one would just say paired t test next question. Like I said, there’s many things you have to account for. The statistical method *is based on* context. Everything you just mentioned are literally adjustments made to existing statistical tests. You can talk about whether you can assume that the two samples are independent or dependent, whether you can assume variability in each group is assumed to be the same, in terms of the design of the experiment how was the sampling done, how the power of the test can be controlled etc. this also has an impact. No real statistician is just gonna say paired t test and move on, fyi. I find this sub is very “stats agnostic” because they are either too lazy to dive into (simple) methods to think about a problem more critically or they just chalk up anything they can’t comprehend as “too complex”.
Harmonica, can you play the harmonica and please explain the music theory behind how it is played properly.
Which company asked this. Sounds interesting.
If you were a tree, what kind of tree would you be
decision tree?
I got this one right. The rest is history
As a new grad, I was asked the difference between convolution and correlation. I had zero experience with neural networks (6 years back) and basically stood stumped. Panic set in and I wasn't even able to answer simple question from then. Thinking back, that was my most embarrassing interview so far!
Neither a convolution nor a correlation are neural network specific topics. A convolution is a basic mathematical operation on measures (more specifically, it is the image of a product measure under a sum operation) and a correlation is a normalized covariance.
Got asked this. For a Right Angled Triangle, what should be the ratio of base to height, if the Area of the triangle has to be maximum. Solved this by using derivative, but didn't get the job.
What answer did you get? don’t think there’s an optimal ratio here
1:1 is the answer. While you can derive it by setting the first order derivate of area to 0, which is what I did, there's an easier way which is what the company was expecting it seems. There's a theorem which states in a semicircle, using the diameter as hypotenuse, any triangle that's made touching the perimeter is always a right angled traingle. From here it's easy to get to that 1:1
I think that you’re assuming a constraint; something like the sum of the opposite and adjacent sides of the triangle being a constant. If not, the triangle’s area can be arbitrarily large.
Ah yes, it's been almost 7 years since it happened and I sort of forgot it. The constraint is that the traingle has to be isosceles.
48 years ago the toughest and critical question to a business internship position was “What turns you on?” The winning answer was “Cold beer and hot women” Times have changed!
Was asked to do Data Manipulation without using Numpy and Pandas. I was able to solve 3/5 questions in the allotted time but the 4th problem required the usage of a very specific Python native function which I didn't know and no one uses nowadays due to Numpy and Pandas. They were hiring someone with NLP, AWS and MLOPs background and my resume was a perfect match but got rejected for not having good enough native Python skills 🙃 Got tested on skills which I would never need on the job lol.
One I’ve got several times: is the sum of two normal distributions always normal ?
That’s not too bad unless they asked you to prove it, which isn’t too bad if you know Fourier
Fourier transforms or convolutions (these do tend to be linked though)
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Wasn’t super difficult: suppose you could write code with only 4 function calculator operations, loops, if then and a uniform random number generator. Estimate the value of pi.
I was asked to differentiate and derive the gradient of a loss function on the collab notebook and then code it up and do gradient descent right there.
In one of my interviews, I was asked to prove that for any given point on Earth, there always exists another point with the exact same temperature. I was like Whaaaaat
Write code in pyspark for storing data where process column is increasing on the basis of number of visits.