The hardest question you’ve been asked in a data science interview

Edouard Harris
Jun 06, 2020

Contents Outline

The hardest question you’ve been asked in a data science interview

Jun 06, 2020 5 minutes read

I work at a YC company that has a evolved an interesting internal Slack group of data scientists. It’s a private group, but recently it got some attention on Twitter and we figured it might help aspiring data scientists if we published a few of the conversations we’ve been having on there. Twitter agreed, so that’s what I’m going to do today.

The first conversation I’m going to post started with a question that one of our Fellows asked the community: What’s the hardest question you’ve been asked in a data science interview?

(I’ve changed the asker’s name below, but a few of the participants kindly agreed to share their full names and links to their online profiles.)

Susan Pan asks:

What’s the most difficult question you ever encountered in a data science interview?

I’ll share mine: “How many years of experience do you have in language X?” This is really hard to answer: Do I count the years I used it in academia? Do I count the years I used it in my hobby projects? Do I count the years when I used it at my job, but just during 15% of my time?

I once decided to answer this question by asking the interviewer, “Can you please elaborate?” I think the interviewer thought I was crazy.

Hoping to hear your most difficult questions and maybe we can share pointers on how to answer them!

Ray Phan
’s answer:

Here’s mine: “If you had to pick one technical problem that was the most difficult for you, explain what it is and how did you approach solving it?”

The reason why this is deceivingly difficult is that it opens you up to questions as you go. They can decide how far or how deep they want to investigate each and every part of your approach. In fact, this is one question I ask all the time when I interview someone. You can quickly determine whether someone really knows how to solve the problem, or if they rode on someone else’s coattails.

Interestingly, this is the only question Elon Musk asks during interviews. (Source: He personally interviewed me when I was applying to Tesla’s Autopilot Program.)


Thanks for sharing! With this question, are you testing a candidate’s problem-solving approach or their depth of understanding of technical concepts or a mixture of both?

Mixture of both.
I want to see how good they are at approaching a relatively unknown problem given their skill set at that point in time, what skills and approaches they learned throughout the whole process, and their problem-solving ability to determine if they successfully solved it.

By the way they answer my follow-up questions as well as the level of detail they share with me with regards to how they solve it, it gives me a pretty good idea on whether they’re someone who can work independently, can work in a group (as they’re explaining the concepts to me and I dig further) and whether I would trust that person at the end of the day.
This is why I said this question is deceivingly difficult because it tells me pretty much everything about the person’s aptitude in a single question.

My problem right now would be: I could tell you about what truly was the hardest problem that I ever faced, but then I would have to admit that I did poorly at the time. Really poorly. I realize this is a potential place for me to show growth, but I would ultimately first have to admit that I initially fell flat on my face.
If you were to interview me, would you appreciate the honesty? Or would you recommend maybe picking the second hardest problem I ever faced instead, maybe one where I did less miserably?


I would want you to admit that to me and tell me why. Growth is also something I look for and if you didn’t learn anything from that, then I wouldn’t hire you — and if the conversation is cut short, I’d jump to the second problem!

Fair. Thank you! I certainly need to practice these sort of interview questions.
Part of my mentorship that I do with my mentees is exactly this line of questioning. I usually split it up into 4 sets of interviews to make sure the mentee is prepared.
(1) Prescreen
(2) Technical fit ← The question I mentioned above goes here
(3) Business Acumen
(4) Culture Fit

What I try to do is ask questions they wouldn’t be expecting — which is also why I stress to them to not prepare for my mock interview sessions.
But yes, practice! Your mentor will hopefully do the things I just said.

The full conversation was a bit longer than this, and it got a couple of other answers. But Ray’s was my favorite, because the interview question he gives forces you to set your own level of difficulty. If you pick a technical problem that’s too easy, you might look bad; but if you pick a one that’s too hard, you might mess up its solution, and also look bad! So you have to pick the hardest problem you’re pretty sure you can solve — which is the whole point of the question.

It’s also interesting that this is the only question that Elon Musk asks during his interviews. That’s something I didn’t know about.

I’m thinking about posting more of these Slack conversations in the future. So if you’re interested in seeing the other answers in this conversation (or in seeing others ones), hit me up on Twitter and let me know. My DMs are open if you have any questions.

Join our private community in Discord

Keep up to date by participating in our global community of data scientists and AI enthusiasts. We discuss the latest developments in data science competitions, new techniques for solving complex challenges, AI and machine learning models, and much more!