2016 Data Science Salary Survey results

September 15, 2016
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

O'Reilly has released the results of the 2016 Data Science Salary Survey. This survey is based on data from over 900 respondents to a 64-question survey about data-related tasks, tools, and the salary they receive from doing/using them. The median salary reported in the survey was US$87,000; amongst data scientists in the US, the median salary was US$106,000.

Appropriately for a survey about data science, O'Reilly doesn't merely report aggregate statistics from the survey; they fit a linear regression model for a data, and extact coefficients from the model indicative of salary "bumps" (or downgrades) attributable to demographic factors. (The model apparently includes no interaction terms.) Factors that tended to increase salary included: working in cloud computing environments; working with Python; and being older. Factors that tended to decrease salary included: in the Education industry, working with Excel, and being female. (Since this is a regression model, that means female data scientists earned $7,800 per year less than their male counterparts for doing the same work.)

The survey also reports on use of tools, and the top 3 in each category were as follows (respondents could select multiple tools in each category):

  • Operating Systems: Windows 74%; Linux 49%; Mac OS X 42%
  • Databases: MySQL 37%; Microsoft SQL Server 33%; Oracle 23%
  • Programming languages: SQL 70%; R 57%; Python 54%

Interestingly, the survey also reported on the tasks that data scientists perform: over 90% reported soem kind of coding in their day-to-day work. The tasks reported, in order of frequency or reporting and shown with corresponding salary ranges of the subset, are shown below:

Data science salary

For much more data and analysis from the 2016 survey, follow the link below to download a free copy from O'Reilly.

O'Reilly: 2016 Data Science Salary Survey

To leave a comment for the author, please follow the link and comment on their blog: Revolutions.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers


Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)