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re: python vs. R I haven't done python at all, but from reading bits and piece online, it seems to me that Python is a lot more about ML than Statistics. Also

re: python vs. R I haven't done python at all, but from reading bits and piece online, it seems to me that Python is a lot more about ML than Statistics. Also, how does one decide what is a "data scientist"? Is it only people who do Stats+ML+IT? What about a researcher in economics or biology? Or marketing. Are those included? They do a lot of Stats and increasingly a lot of ML. Not so much information technology though (less concerned with data storage and retrieval, because they have other people to do that for them). I'd venture to say that researchers like that are far bigger number than pure play data scientists and would be interesting to see the technical skills for them. I bet SPSS and SAS would look a lot more in demand.

gnaddel 12y ago
Just my personal biased perspective: You are correct, there is no good definition of "Data Science". Just as any other buzzword, it is widely devoid of meaning but useful to convey a general idea to certain audiences. Regarding R vs. Python, I personally use Python to process my data up to the point where I can hand it over to R in a convenient df-esque shape and use R for stats and plotting. Even if I do not require R for stats, I still use ggplot2 for plotting, though I'd be happy to see Seaborn or Bokeh evolve to a point where they can rival it.
sososoko 12y ago
You can take a look at this book Analyzing the Analyzers The Authors surveyed data scientists, asking about their experiences and how they viewed their own skills and careers.They answer your question what is a "data scientist" http://www.oreilly.com/data/free/files/analyzing-the-analyzers.pdf http://www.oreilly.com/data/free/files/analyzing-the-analyze...
- blumkvist 12y ago
  That's a great paper. I wonder how I've missed it. I'm happy to to say that it partially confirms my own take on the situation. I thought of it only in 2 categories - Comp sci/math guys vs. Applied statistics guys (mostly from Humanities). Reality seems more nuanced then that (as always). Very nice read!
raus22 12y ago
The answer to what a data scientist does, is very different when you ask a self-proclaimed data scientist and a person that hires a "data Scientist". This creates can create disappointment on both sides. It ranges (from the hiring side) from: "good if you know excel and you will report figures to management" to "please only apply if you have 2 Ph.Ds and 20 years of experience in C". So it is a bit wide... the self-proclaimed "data scientists" probably goes from know a programming language/know visualising/know statistics up to "X Ph.Ds and Y years of experience where Y > 20"

gnaddel 12y ago

Just my personal biased perspective: You are correct, there is no good definition of "Data Science". Just as any other buzzword, it is widely devoid of meaning but useful to convey a general idea to certain audiences. Regarding R vs. Python, I personally use Python to process my data up to the point where I can hand it over to R in a convenient df-esque shape and use R for stats and plotting. Even if I do not require R for stats, I still use ggplot2 for plotting, though I'd be happy to see Seaborn or Bokeh evolve to a point where they can rival it.

sososoko 12y ago

You can take a look at this book Analyzing the Analyzers The Authors surveyed data scientists, asking about their experiences and how they viewed their own skills and careers.They answer your question what is a "data scientist" http://www.oreilly.com/data/free/files/analyzing-the-analyzers.pdf http://www.oreilly.com/data/free/files/analyzing-the-analyze...

blumkvist 12y ago
That's a great paper. I wonder how I've missed it. I'm happy to to say that it partially confirms my own take on the situation. I thought of it only in 2 categories - Comp sci/math guys vs. Applied statistics guys (mostly from Humanities). Reality seems more nuanced then that (as always). Very nice read!

raus22 12y ago

The answer to what a data scientist does, is very different when you ask a self-proclaimed data scientist and a person that hires a "data Scientist". This creates can create disappointment on both sides. It ranges (from the hiring side) from: "good if you know excel and you will report figures to management" to "please only apply if you have 2 Ph.Ds and 20 years of experience in C". So it is a bit wide... the self-proclaimed "data scientists" probably goes from know a programming language/know visualising/know statistics up to "X Ph.Ds and Y years of experience where Y > 20"