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I've recently been looking for top-of-the-line statisticians in a recruiting process for our company. Myself, I'm a Physics Engineering major. I gather that great mathematical statisticians have studied a bit different courses, and much more in depth.

When evaluating a candidate, are courses a good indicators of this person being excellent?

Preferably we're talking graduate or post-graduate level.

We're looking to fill roles of data miners, statistical modeling and data visualization. Thanks Chris, for the suggestion to clarify.

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  • $\begingroup$ If someone wants to re-tag this question I'd be happy. I couldn't with my low rep. $\endgroup$
    – John Sjölander
    Commented Feb 4, 2011 at 14:00
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    $\begingroup$ this question is off-topic, so I will comment instead of answering. Ask about M-estimators. Or pick any problem from Assymptotic Statistics by van der Vaart. The only one problem with this question is that you cannot say that the interviewee is not excelent if he(she) did not answer. If on the other hand he (she) does answer, excellency is pretty much guaranteed. This is of course IMHO. $\endgroup$
    – mpiktas
    Commented Feb 4, 2011 at 19:15
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    $\begingroup$ @mpiktas Are you saying that knowledge of asymptotics will assure that one is excellent at visualizing data? There seems to be little to connect the two. Indeed, that's the problem with this entire question: its premise is that excellence in data mining, stats modeling, and data visualization requires "great mathematical statisticians" who have taken lots of courses. Neither one of those criteria--being mathematical or taking courses--seems to be closely related to succeeding in such positions. $\endgroup$
    – whuber ♦
    Commented Feb 4, 2011 at 21:08
  • $\begingroup$ @whuber - I'm not claiming it to be the only way, nor the best way. I'm hoping that it'll be a nice addition to an already extensive and exhaustive recruiting process that hopefully is more effective than asking the man on the street. $\endgroup$
    – John Sjölander
    Commented Feb 5, 2011 at 7:54
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    $\begingroup$ Ask them in advance to present a procedure for ranking applicants. ;) $\endgroup$
    – abaumann
    Commented Oct 9, 2012 at 14:43

3 Answers 3

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It really depends what your company is doing. Are you looking for machine learning experts? Data visualisation experts? Data mining experts?

When I interview statistics PhDs I like to ask them questions about linear regression, as I feel that anyone claiming to be an expert in statistics should at the very minimum be able to explain linear regression to me, and it's surprising how many can't.

Apart from that I'd consider it to be a good sign if they can have a good discussion about model selection/validation procedures, the concept of training and validation sets, cross-validation etc. If they know about classification algorithms (k-NN, SVM, decision trees etc) and can discuss their strengths/weaknesses that's even better.

I find that the particular courses they've studied are rarely a good indicator, and are only really useful for steering the discussion in the interview. If they're claiming to have studied something on their CV, I expect them to be able to discuss it at length.

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  • $\begingroup$ I've edited with your suggestion to clarify, if you'd like to add anything. $\endgroup$
    – John Sjölander
    Commented Feb 4, 2011 at 13:51
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    $\begingroup$ It's interesting that you don't feel any specific courses are good indicators. In comparison, I've found that when interviewing programmers, great programmers have often studied any combination of Advanced Algorithms II/III, Cryptography, Paradigms of Programming languages, or Compiler Construction. If their grades in those are good they seem more likely to be good programmers. $\endgroup$
    – John Sjölander
    Commented Feb 4, 2011 at 13:55
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    $\begingroup$ @John Things have changed. When I was hiring programmers in the late '80s, two tests emerged as the most reliable indicators of actual performance. The first was typing ability(!) and the second was any ability at all to do trigonometry. The former was related (quite crudely but effectively) to experience and the latter was related to capacity for abstract thinking. I suspect your list of courses might be measuring something similar to the latter. $\endgroup$
    – whuber ♦
    Commented Feb 4, 2011 at 21:16
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    $\begingroup$ The problem with looking at courses studied is that courses with the same name at different universities can vary widely. Knowing that someone has studied 'Advanced Algorithms' tells me very little about what they actually know, even less about whether they can apply that knowledge in their job, and less still about whether they can effectively explain what they're doing to someone with a non-technical background. $\endgroup$
    – Chris Taylor
    Commented Feb 6, 2011 at 15:12
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I agree with Chris on most of what he says. Additionally, I'd like to add that without knowing the institutions or universities in detail, just looking at grades would be very misleading. I could easily give a relevant example; I have recently graduated with a masters in engineering mathematics; and taken a variety of statistics courses (with good grades) but I couldnt work in any statistics intensive job right now. That doesn't mean that my uni sucks, but mostly that I didn't manage to learn much out of my statistics courses during university...

Apart from the candidate's knowledge on statistics, I'd also highly value good communication skills; as any cross-disciplinary project eventually boils down to communication problems between experts of different fields. Any test on how well the candidate can share his expertise with others should be a good measure on that.

Furthermore, good computer/programming skills (and no just R is not enough, IMHO) is surely a big plus. If the person has some background in mathematical modeling, it'd be a cherry on the cake :)

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  • $\begingroup$ What you say makes sence. We use the information on courses and grades as one of many data points to make sense of a greater picture. $\endgroup$
    – John Sjölander
    Commented Feb 5, 2011 at 7:50
  • $\begingroup$ Thanks! Of course, I figured you would not base your selection process on grades, I merely tried to present an alternative perspective. I have a number of friends that are devoted programming geeks, that never cherished under the rigidity of university education. Anyways, as long as you stay open minded about the strengths and weaknesses of the candidates, I am sure you'll get great team members eventually. :) $\endgroup$
    – posdef
    Commented Feb 5, 2011 at 13:56
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Chris really nailed the data minining stuff. If you need someone who can also look at experimental data, you can stop all but the most versatile of statisticians dead in their tracks by asking them to explain a split-plot experiment.

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