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How can a data scientist actually complain that the low value data munging work is already done for him ? Gosh, it should be the other way around - we should complain about how much of this we have to do at work !
Earlier quoted context omitted.
To me it sounded more like "the problems they do at Mathematical Olympiads are not the real mathematics done at academia/the enterprise," which turns out to be quite true in many ways.
Not just math -- even the problems done at programming contests have fairly little to do with programming! I've worked at Google for nearly 10 years -- not sure I can solve the Google code Jams :) Or at least I haven't been motivated to do so. I know all my basic data structures and algorithms, but the questions don't seem that motivating.
I'm sure you meant it has fairly little to do with day-to-day programming for the majority of software engineers, which is correct.
Regarding the article, I also disagree with it. I feel like the author is saying "algorithms != programming contests" which is false. Algorithms are the essence of programming contests, just like 'machine learning' is the essence of Kaggle competitions. Open up Bishop's "Pattern Recognition and Machine learning" and you won't find anything about "deploying your model to production", but you will find lots of math on how to build models because that is what ML is. What the author seems to be describing is data-science.