This is an update to our December 2013 article: 6000 companies hiring data scientists.  Microsoft and IBM still dominate, but we've seen some shift over the last 12 months:

  • Accenture, Google and Cognizant are gaining traction, but overall, rankings for top companies have barely changed
  • The top 20 companies now amount to 7.5% of data scientists, versus 10% in December 2013. This is a significant change, proving that data science adoption is exploding faster in small companies.
  • We have now 7,500 companies in our listing, versus 6,000 in December: a 25% growth over the last 12 months.

Note that data science is still growing very fast. Also, the number of data scientists per company (the statistical distribution), as a function of company size, follows a Zipf distribution.    

We will soon publish a more detailed article with a breakdown per industry, and based on two LinkedIn profiles, not just mine. This will allow for increased accuracy, and more refined trend analysis. Below are the top 20 companies today, based on 10,000+ connections on my LinkedIn profile (the drops or gains in rank, among the top 20 companies, compared with December 2013, are not statistically significant except for one company).

You can download the list of 7500 companies here. We will also use this data set (a more granular version) to update our list of top job titles for data scientists. Many more interesting articles are in our pipeline, including:

  • full code and example (with Excel spreadsheet, and source code in a scripting language) for our Jackknife regression (based on highly realistic simulated data about the value of specific data science software skills)
  • hidden decision trees applied to real data (source code and Excel implementation)
  • More about reverse-engineering some Google algorithms
  • Taxonony for top 2,000 data science articles (and how to use it for growth hacking)
  • Skills mix broken down by age, education level, gender and location, for data scientists
  • Skills associations, for various types of data scientists

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Comment by Vincent Granville on February 2, 2015 at 6:41am

Many data scientists have a PhD, and Amazon contacted me many times for such positions. Microsoft to a lesser extent.

Comment by Sione Palu on February 2, 2015 at 2:26am

I'm surprised that the big vendors like IBM, Microsoft, Google, Amazon, etc,... are hiring positions for data-scientists. Traditionally as has been for at least a decade (Amazon is a late comer), those companies have been hiring doctoral candidates (computer science, math, stats, engineering, etc...) because most of their work is published in various journals. That's the main reason, because those doctorate candidates have R&D experience and when they submit their draft of their manuscript for publication, they make sure theirs is original & be fully aware of past similar work by other scholars so that they make no mistake in claiming what they published as something original or new when in fact it has been done in the past. For example, Prof Susan Dumais at Microsoft Research (http://research.microsoft.com/en-us/um/people/sdumais/) who had done early work on latent semantic indexing, have a job title as a computer-scientist not data-scientist and in fact , her work is pretty much data-science. She's still publishing her work to date.

Comment by Vincent Granville on January 29, 2015 at 9:23am

Hi Glenn, we plan on updating very soon our list of hundreds of alternate job titles for data scientists.

Comment by Glenn Strycker on January 29, 2015 at 6:09am

Hi, Vincent -- I think I may be your one contact from Conversant, but there are many more of us here!  We actually have a full Decision Sciences team and several Analytics teams, but none of our job titles or descriptions have "data science" or "data scientist" in them.  Can you comment on the various job titles and job descriptions that people use that differ from data science / data mining / analysis?  These terms are becoming over-loaded, IMHO.

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