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Comment by joker3 | Hacker News Reader

> For myself, it was worth noticing that Statisticians and Actuaries are at the bottom of the heap as a prior role for existing data scientists.

This has a lot more to do with the relatively small number of statisticians and actuaries out there than it does the odds of people from various backgrounds transitioning into data science roles.

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Exactly. The data is about the backgrounds of data scientists, but is incorrectly interpreted as the probability of becoming a data scientist given a certain background. Obviously the two are related (Bayes' theorem), but to draw any conclusion one would need to know the number of PhDs, Masters, etc. that are applying to become data scientists. For example, the fact that a small fraction of data scientists has a MOOC degree does not imply that the probability of becoming a data scientist if having "only" a MOOC degree is low. For all that we know the few people in the market having this kind of non-traditional preparation could have 100% success rate in getting those jobs.

(Which seems like the kind of thing you would hope someone applying to Data Science positions would have considered.)

Actuaries are trying hard to market themselves against “data scientists”. Adding basic intro to statistical learning type material and r programming to their exam syllabus.

One can get an idea of the relevant frequencies from table 13 of the doctoral completion survey here [1].

[1]https://ncses.nsf.gov/pubs/nsf19301/data

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