3 ms·

I believe the core of what you're saying: it's fairly rare to find someone who is algorithmically excellent, and who already knows all of the details of web de

by timr 13y ago

I believe the core of what you're saying: it's fairly rare to find someone who is algorithmically excellent, and who already knows all of the details of web dev. But I think that's largely a matter of interest and specialization, not capability. But I stand by my larger point: I wouldn't hire a web dev who wasn't fluent enough in basic CS that they couldn't pass an algorithm interview. They don't need to be able to design machine learning algorithms, but things like basic algorithm analysis are essential.

nostrademons 13y ago
I don't think we really disagree: I also wouldn't hire a web dev who wasn't fluent enough in basic CS that they couldn't pass an algorithm interview. Once you get past JQuery and need to do your own DOM manipulation, it becomes really important to have your tree traversals down. And webdevs who don't realize that NodeLists are actually lists (with O(N) .length calls) cause a world of pain with their for(var i = 0; i < element.children.length; ++i) quadratic loops. But I thought what started this thread was mamcx's thought question about why we don't apply this the other way around: when hiring data scientists, why do we not require that they have a basic fluency with web UIs, at least enough to throw a table and a few images up onto a web page and show/hide some details? In my experience, what separates the best data scientists from the worst - and there's an order of magnitude difference in productivity between them, at least, enough that a poor data-scientist will never come up with a useful result - is the ability to quickly visualize their data set and understand its "shape". They need to know the distribution, and be able to drill into a few examples of raw data, and come up with the top X or so results by whatever signal they're studying. And the easiest way to do this is by generating a web page with a few charts, a few examples, a sortable table, etc. Nothing terribly fancy, but having the chops to do this on your own makes you much more effective than someone who knows the theory but can get their hands dirty with actual data.
- timr 13y ago
  Yeah, I think we're on the same page. Your traversal example is a good one. I also agree with you that web engineers should be at least functionally competent at UI development. But where I depart from mamcx is that I'd still choose the algorithmically talented candidate over the one with UI skill and no algorithmic knowledge. I think that learning web UI development is easier than learning the fundamentals of computer science. But maybe I'm just a snob. :-)

by timr 13y ago

nostrademons 13y ago

I don't think we really disagree: I also wouldn't hire a web dev who wasn't fluent enough in basic CS that they couldn't pass an algorithm interview. Once you get past JQuery and need to do your own DOM manipulation, it becomes really important to have your tree traversals down. And webdevs who don't realize that NodeLists are actually lists (with O(N) .length calls) cause a world of pain with their for(var i = 0; i < element.children.length; ++i) quadratic loops. But I thought what started this thread was mamcx's thought question about why we don't apply this the other way around: when hiring data scientists, why do we not require that they have a basic fluency with web UIs, at least enough to throw a table and a few images up onto a web page and show/hide some details? In my experience, what separates the best data scientists from the worst - and there's an order of magnitude difference in productivity between them, at least, enough that a poor data-scientist will never come up with a useful result - is the ability to quickly visualize their data set and understand its "shape". They need to know the distribution, and be able to drill into a few examples of raw data, and come up with the top X or so results by whatever signal they're studying. And the easiest way to do this is by generating a web page with a few charts, a few examples, a sortable table, etc. Nothing terribly fancy, but having the chops to do this on your own makes you much more effective than someone who knows the theory but can get their hands dirty with actual data.

timr 13y ago
Yeah, I think we're on the same page. Your traversal example is a good one. I also agree with you that web engineers should be at least functionally competent at UI development. But where I depart from mamcx is that I'd still choose the algorithmically talented candidate over the one with UI skill and no algorithmic knowledge. I think that learning web UI development is easier than learning the fundamentals of computer science. But maybe I'm just a snob. :-)