Data Scientist Job Analysis

A few weeks ago, I posted 16 Companies Hiring Data Scientists Right Now. I decided to do a bit of analysis on the job posts, so I took all the job posting and compiled them into one file.

The Problem

I wanted to determine 2 things:

  1. What words occurred most often in the job posts?
  2. What words occurred in the most jobs posts?

The questions are similar, but if you read closely, they are different.   I wrote some Java code to answer those questions. The raw results are posted here.

Results

Honestly, nothing too surprising showed up. Not counting the common English words (and, to), the word data was the most popular. It occurred 167 times and it occurred at least once in all 16 job postings. That makes sense; a data scientist should know about data. I thought hadoop would occur in all job descriptions but it only appeared in 11 of the 16 job descriptions. Here are some other words I found interesting:

  • statistical occured 29 times and in 10 job descriptions
  • analysis occured 46 times and in 13 job descriptions
  • analytics occured 22 times and in 6 job descriptions
  • statistics occured 16 times and in 9 job descriptions
  • machine learning occured 14 times and in 9 job descriptions
  • phd occured 11 times and in 11 job descriptions
  • sql occured 12 times and in 10 job descriptions

On an interesting note, Python and R occurred in more job postings than Java (2 more to be exact).

Does anything in the results strike you as interesting?

2 thoughts on “Data Scientist Job Analysis”

  1. Apparently, a Ph.D. is considered of great importance to the people who want to hire Data Scientists, despite the fact that Data Science is a relatively new discipline with few related formal education programs available. Hmm.

    1. Hi Paul,
      I found that interesting as well. I have a feeling that many current data scientist positions focus heavily on machine learning and statistical analysis. Thus, a PhD is a big plus for that type of a position. However, I think in the future that will change a bit. A data scientist needs to do more than just tune a sophisticated algorithm (ask the right question, find the data, help the business,…)

      Thanks for commenting

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