R Passes SAS, but Python Leaves Them Both Behind
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Re: R Passes SAS, but Python Leaves Them Both Behind
#2There is a question regarding the definition of "data science jobs." The author explains his methodology in a lengthy report http://r4stats.com/articles/how-to-search-for-data-science-j...
The issue is what is "data science" really? In what respect is it different from traditional statistics and data analysis and not just a new buzzphrase?
Probably many jobs using SAS could be considered "data science" but don't use the specific buzz words and phrases that the author specifies in his methodology to identify "data science" jobs. Thus, the headline that "R Passes SAS" could be inaccurate, except in the sense that R is more popular among statistics and data analysis jobs that use "data science" buzzwords and phrases.
Re: R Passes SAS, but Python Leaves Them Both Behind
#3Nice data munging out of Indeed.com here. The article author gives a detailed description of searching Indeed in a write-up linked from the original article as well (http://r4stats.com/articles/how-to-search-for-data-science-j...).
Just playing around with the search terms from that second linked article is also interesting - it would appear that many terms ("machine learning", "data science", "predictive modeling", some others) show that Amazon has the largest number of job listings from a single company - for "machine learning" Amazon shows 1706 listings out of 12499 or almost 14% of all listings . . . The way Amazon also pops out in other data science term searches is also interesting - at least in their job listings, Amazon seems to really be attempting to slurp up candidates with deeper data and stats skills.
For some time I have been somewhat cynical about data science. My impression has been that much of what has been pushed as data science jobs is thinly veiled data reporting gigs (just plain old business intelligence). While I still think data science is over-hyped, I think I need to reconsider just how critical it will be as a knowledge base or skill set. While there may not be a large number of deep learning jobs out there, the expectation that a data hacker can be expected to perform a linear or logistic regression against a set of gathered and cleaned data may be closer to fizz buzz than I previously assumed.
I am teaching an introductory programming class (using Python) this semester and students are definitely focused on data science as a career track.
Re: R Passes SAS, but Python Leaves Them Both Behind
#4There is a question regarding the definition of "data science jobs." The author explains his methodology in a lengthy report http://r4stats.com/articles/how-to-search-for-data-science-j... The issue is what is "data science" really? In what respect is it different from traditional statistics and data analysis and not just a new buzzphrase? Probably many jobs using SAS could be considered "data science" but don't use…
SAS is also a huge iceberg, without much in the way of open source culture that lends itself to visibility. A lot of SAS happens behind closed doors at megacorps.
Re: R Passes SAS, but Python Leaves Them Both Behind
#5I'm surprised that the author combines "the C languages" saying that most adverts that mention any of C/C++/C# mention all three. In my experience there is a large difference between companies searching for C# developers and those searching for C/C++. After blurring this distinction he concludes that R and Python are "very different languages" while I consider them to be largely overlapping.
Re: R Passes SAS, but Python Leaves Them Both Behind
#6I hate these sort of comparisons. You've got R, Python, SAS... okay, those are sort of similar. Then you've got Java and "C, C++ or C#," and man, including C# with C/C++ is... fraught. Then you've got Hadoop, Spark, Hive... okay, those are all kind of different from what we've had so far. Now you've got Tableu and RapidMiner. Uh. In the second chart, "Microsoft" is included as a keyword. Okay. It's just... comparing apples, oranges, bananas, grapes and pears. What's it supposed to tell us?
Re: R Passes SAS, but Python Leaves Them Both Behind
#7There is a question regarding the definition of "data science jobs." The author explains his methodology in a lengthy report http://r4stats.com/articles/how-to-search-for-data-science-j... The issue is what is "data science" really? In what respect is it different from traditional statistics and data analysis and not just a new buzzphrase? Probably many jobs using SAS could be considered "data science" but don't use…
SAS is also a huge iceberg, without much in the way of open source culture that lends itself to visibility. A lot of SAS happens behind closed doors at megacorps.
Also notable that so many new shops are foregoing it entirely. SAS, and its price tag, is a holdover from the days when 'analytics' was an afterthought for companies looking to maximize profit.
Now that much less mature companies are realizing the value of 'analytics' (I hate that word) SAS's cost doesn't really make sense.
Re: R Passes SAS, but Python Leaves Them Both Behind
#8I'm surprised that the author combines "the C languages" saying that most adverts that mention any of C/C++/C# mention all three. In my experience there is a large difference between companies searching for C# developers and those searching for C/C++. After blurring this distinction he concludes that R and Python are "very different languages" while I consider them to be largely overlapping.
Agreed.
So far in my search, C# leans toward Microsoft shops seeking C#/.NET whereas C/C++ has been companies searching for embedded software roles.
Re: R Passes SAS, but Python Leaves Them Both Behind
#9I'm glad to see the quick convergence on Python. I've evaluated Python every ~2 years since 2006 for "data science" tasks (machine learning, statistics, data munging, and visualization). I'd argue that Python only properly covered this full data science stack 1.5-2 years ago. R covered this stack adequately probably around 2011-2012. Matlab had this before 2005.
What makes Python a superior language to Matlab and R is the ease of software development. It's an easy, pleasant language to work in, and I trust it for production tasks (I've written production R code and it's fairly hard to read and fragile).
What's even better is data science is moving 100% into Python 3 (from 2) by 2020:
Re: R Passes SAS, but Python Leaves Them Both Behind
#10There is a question regarding the definition of "data science jobs." The author explains his methodology in a lengthy report http://r4stats.com/articles/how-to-search-for-data-science-j... The issue is what is "data science" really? In what respect is it different from traditional statistics and data analysis and not just a new buzzphrase? Probably many jobs using SAS could be considered "data science" but don't use…
SAS is also a huge iceberg, without much in the way of open source culture that lends itself to visibility. A lot of SAS happens behind closed doors at megacorps.
Even some of the mega corps want to get away from SAS. A friend of mine who does data analytics at the power company told me they want to bring on more Python developers despite their regulators wanting things done in SAS.