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:
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