
How I Became a Data Scientist Despite Having Been a Math Major - johndcook
http://stiglerdiet.com/blog/2015/May/11/how-i-became-a-data-scientist/
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shruubi
Read as: how I became a data scientist after taking an appropriate and helpful
major

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j2kun
The problem with not having a math background is that you will succumb to all
the people who throw around buzzwords but don't know what the hell they're
talking about. You need to be able to recognize (and assert authority over)
someone whose first thought is that "support vector regression and a bayesian
net" is the right way to go. Or, to put it nicer, refine their thought into
something useful.

The problem with not having a software and "grungy coding skills" background
is that you aren't able to efficiently reproduce/check/verify claims being
made which are often wrong or misleading. A recent example I had of this is
someone studying how an algorithm behaved on a subset of interest of a
particular population, and they didn't even bother to check that the subset of
their data was statistically large enough to draw any conclusions (only 17
records out of thousands). Needless to say this example also failed on the
reproducibility and reuse fronts.

The problem with both in academia (even at polytechnic non research schools)
is that they don't know enough about each other.

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mojoe
Question for the data scientists out there: is it more straightforward to
become a data scientist from a software engineering background or from a math
background? Data science is a varied field, but from what I've heard a lot of
the work is munging data (which is a fairly easy task for a skilled software
person).

Also, I'm glad the author added the twitter endorsement to the article --I've
been considering creating a twitter account, and the fact that the author
found it so useful helps with my decision to devote time to creating an
account.

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lessthunk
The perfect data scientist -- imho is great at massaging data and has a ton of
real life experience with real data; So somebody on the interface of
statistics and computer science is best.

Computer scientists mostly don't know about sampling and make easy problems
hard. Statisticians mostly fail at simply getting the data in a format they
need.

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huac
Perhaps PhD math programs don't hold your hand through teaching data science,
but it isn't a horrible way of preparing you for a (first) job in data. Color
me impressed when a history major picks up data science!

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Gmo
Yeah, I confess I only read the title, but I don't understand the "despite".

I mean, surely, you need a good background in mathematics to model and extract
meaningful information from the data, so I don't see how it is crazy to do
that with a PhD in mathematics ...

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mauricemir
I think his point was that pure math can be very devolved from real world as I
found when i tried to go from a Engineering to a HNC in Maths Stats and
Computing.

Back then it was virtulay all Pure maths with the computing side being shall
we say Antique - most of my course mates where working at Tier 1 RnD workng at
the bleeding edge, my employer hired the first non academic knowledge engineer
in the UK

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dschiptsov
Begin with Andrew Ng's mooc at coursera, to get the basics and the feel of it.

I've completed the very first his course in December 2011.

