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I'm getting curious about all these online predictive challenges going on, such as DREAM, Kaggle and Innocentive. Surely they all are good occasions to work on new projects and new ideas, to know other collaborators, to get important training about science, and to possibly win some money

And also they could represent a good point in one's resume. So I was wondering: in job application processes (in both industry and academia), do candidate selectors care about the participation of the candidate in any of these challenges?

If yes, how much?

If no, why not?

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2 Answers 2

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At the very least, it shows you are actively interested in the subject. Participation can be enough to show you are more enthusiastic about the subject than other applicants. It is also helpful for entry level data scientist positions where experience isn't necessarily expected, but appreciated. If you have won any competitions, or if you are at the 'Master' Kaggle level, definitely include it.

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I don't think that just "participating" would be an advantage. Because if you paticipate but perform very poorly, it will not demonstrate that you are better or have some special skills. However, if you win some prizes in these competitions or are highly ranked, it would certainly help. It will show that you have good skills in statistics/data mining / etc. Now, how much it would help depends on the candidate selectors and even on the job that you apply for. But if you are highly ranked and win some prizes, it should be positive for your CV.

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    Are you on the selection panel for academic jobs in data mining or machine learning?
    – 410 gone
    Jul 30, 2015 at 6:59
  • I'm not currently on a selection panel but as a data mining researcher, I have discussed both with students applying for jobs in the industry as well as some company who want to hire some employees, and had some industry collaborations.
    – Phil
    Jul 30, 2015 at 16:18
  • @Phil I see your point Phil, but think in life activity is always more valued than inactivity. Nov 13, 2015 at 17:22

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