8 ms·

These questions are largely unanswerable in their current form. Like"estimate the probably of disease in a city given Nationwide has a low probability". Like, w

These questions are largely unanswerable in their current form. Like"estimate the probably of disease in a city given Nationwide has a low probability". Like, what the heck does that even mean. I could imagine a dozen answers. I can only guess they are trying to get you to think about Bayes probability an event occurs given X independent identical trial). But that's ludicrous, because on what world has anyone proved disease occurs uniformly at random?

nerdponx 9y ago
The point isn't to answer the question correctly. It's to show how you think through the problem. There is often a "right" way to approach the problem and a "right" way to answer the question, even if there is no right answer per se.
- ben_jones 9y ago
  I've never understood how there is a "right way to think about something". Isn't it an attribute of humanity that we all think and approach problems differently? Are companies really looking for one single type of individual to clone across all their engineering teams?
  - deleted 9y ago
    [deleted]
  - ImSkeptical 9y ago
    I believe it's not that there is a single right way to think about a problem, but there probably are wrong ways to think about the problem. For example, going through all the issues with the question and implicit underlying assumptions, talking about what you'd need to give a good answer, or the characteristics a good answer may have might not be exactly what the interviewer expected or was looking for - but such an answer could demonstrate your competence in the field and be a good answer. On the other hand, trying to make up an answer, or brazen your way through with jargon while hoping the interviewer didn't notice would likely be a bad answer. It's not that these companies are looking for a single kind of thought. On the contrary, I believe they value different kinds of thought. Instead, they believe they can sort kinds of thought into desirable and not.
    - nerdponx 9y ago
      This is exactly it. Thanks for laying it out clearly.
    - dapreja 9y ago
      The reality is, unless you're directly communicating with someone who understands the problem/question, they'll be expecting the textbook definition as is or whatever stackoverflow response has.
      - nerdponx 9y ago
        In data science interviewing, that generally is the case. Technical people are going to be asking these questions and evaluating you.
- justinjlynn 9y ago
  How I so desperately wish that were true in the general case. Sadly with many large corporations there is one single answer they're looking for and damn the false negatives.
- kafkaesq 9y ago
  The point isn't to answer the question correctly. It's to show how you think through the problem. That's what people always say. Like, as if they actually tell from 1 or 2 of these goofy whiteboarding sessions. It seems the most they can actually glean from these sessions is, "Huh, looks like their problem-solving approach is different from mine. Plus, they come in not having the advantage of having the solution already ready-baked and laid-out for them, in whatever interviewing guide it was I found this problem. Doesn't that suck for them? Not to mention being under pressure from doing way too many, generally carelessly orchestrated interview tracks (in their non-existent spare time) while being stuck in some job they're anxious to quit. And getting distracted by me diddling with my cell phone while they're doing headstands for me. Gosh, why is it so hard to find decent candidates, these days?"
  - nerdponx 9y ago
    There is a lot of cynicism about these types of questions in this thread, but I suspect a lot of it is coming from programmers and not data scientists. As a DS candidate I always find these kinds of interview questions a valuable learning experience and a positive challenge. It also provides me some insight into the kinds of problems they're interested in, and the kinds of approaches they use. When I mean "right approach", I mean that there are several possible approaches, but only one of them is doable in a few hours in the afternoons, where as the others might take a research team and several weeks. Being able to recognize the right approach, and to ask the right clarifying questions, is important for data scientists, in the same way that being able to choose the correct algorithm or data structure is important for (certain types of) software engineers.
    - kafkaesq 9y ago
      Agreed - these questions are definitely more appropriate for research oriented positions. And actually, way more interesting in their own right than most programmer interview questions. What rubs me the wrong way is when, applying for more or less "standard dev" jobs, one gets asked research-grade questions (i.e. "Solve this cute problem I was fed the solution to recently, either in grad school or in some handout my manager gave me just now. But which was actually an open problem in the literature for 5-10 years before a reasonable solution came down the pipe.") For a job that ends up being, "Congratulations on making it through our interview process! Now would you mind debugging this {{horribly written X}} that no on here wants to touch with a 10-foot pole? Everyone here has to do 9-12 months of shitwork before moving on to anything interesting here, you see."
deleted 9y ago
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nerdponx 9y ago

The point isn't to answer the question correctly. It's to show how you think through the problem. There is often a "right" way to approach the problem and a "right" way to answer the question, even if there is no right answer per se.

ben_jones 9y ago
I've never understood how there is a "right way to think about something". Isn't it an attribute of humanity that we all think and approach problems differently? Are companies really looking for one single type of individual to clone across all their engineering teams?
- deleted 9y ago
  [deleted]
- ImSkeptical 9y ago
  I believe it's not that there is a single right way to think about a problem, but there probably are wrong ways to think about the problem. For example, going through all the issues with the question and implicit underlying assumptions, talking about what you'd need to give a good answer, or the characteristics a good answer may have might not be exactly what the interviewer expected or was looking for - but such an answer could demonstrate your competence in the field and be a good answer. On the other hand, trying to make up an answer, or brazen your way through with jargon while hoping the interviewer didn't notice would likely be a bad answer. It's not that these companies are looking for a single kind of thought. On the contrary, I believe they value different kinds of thought. Instead, they believe they can sort kinds of thought into desirable and not.
  - nerdponx 9y ago
    This is exactly it. Thanks for laying it out clearly.
  - dapreja 9y ago
    The reality is, unless you're directly communicating with someone who understands the problem/question, they'll be expecting the textbook definition as is or whatever stackoverflow response has.
    - nerdponx 9y ago
      In data science interviewing, that generally is the case. Technical people are going to be asking these questions and evaluating you.
justinjlynn 9y ago
How I so desperately wish that were true in the general case. Sadly with many large corporations there is one single answer they're looking for and damn the false negatives.
kafkaesq 9y ago
The point isn't to answer the question correctly. It's to show how you think through the problem. That's what people always say. Like, as if they actually tell from 1 or 2 of these goofy whiteboarding sessions. It seems the most they can actually glean from these sessions is, "Huh, looks like their problem-solving approach is different from mine. Plus, they come in not having the advantage of having the solution already ready-baked and laid-out for them, in whatever interviewing guide it was I found this problem. Doesn't that suck for them? Not to mention being under pressure from doing way too many, generally carelessly orchestrated interview tracks (in their non-existent spare time) while being stuck in some job they're anxious to quit. And getting distracted by me diddling with my cell phone while they're doing headstands for me. Gosh, why is it so hard to find decent candidates, these days?"
- nerdponx 9y ago
  There is a lot of cynicism about these types of questions in this thread, but I suspect a lot of it is coming from programmers and not data scientists. As a DS candidate I always find these kinds of interview questions a valuable learning experience and a positive challenge. It also provides me some insight into the kinds of problems they're interested in, and the kinds of approaches they use. When I mean "right approach", I mean that there are several possible approaches, but only one of them is doable in a few hours in the afternoons, where as the others might take a research team and several weeks. Being able to recognize the right approach, and to ask the right clarifying questions, is important for data scientists, in the same way that being able to choose the correct algorithm or data structure is important for (certain types of) software engineers.
  - kafkaesq 9y ago
    Agreed - these questions are definitely more appropriate for research oriented positions. And actually, way more interesting in their own right than most programmer interview questions. What rubs me the wrong way is when, applying for more or less "standard dev" jobs, one gets asked research-grade questions (i.e. "Solve this cute problem I was fed the solution to recently, either in grad school or in some handout my manager gave me just now. But which was actually an open problem in the literature for 5-10 years before a reasonable solution came down the pipe.") For a job that ends up being, "Congratulations on making it through our interview process! Now would you mind debugging this {{horribly written X}} that no on here wants to touch with a 10-foot pole? Everyone here has to do 9-12 months of shitwork before moving on to anything interesting here, you see."

deleted 9y ago

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