Which Data Scientists Earn The Most Money?

O’ Reilly Media’s new salary survey reveals how to earn big money as a data professional: Move to California, learn Spark, and be a man.

Which Data Scientists Earn The Most Money?
[Photo: Flickr user Joel Penner]

O’Reilly Media just published its 2014 Data Science Salary survey, which also identifies the favorite tools of data professionals. The 816 respondents from 53 countries performed a variety of job functions within the data world, the most popular being data analyst (including some coding), statistician, and software developer.


The median salary in the U.S. including non-salary compensation was $144,000. Major industries with the highest median salaries included entertainment ($135,000) banking/finance ($117,000), and software ($116,000).

This being a data science survey the authors created a regression model in order to determine how much different factors affected salary. Regression models can be used to predict the value of one variable based on the values of others, e.g., predict salary based on demographic data or tool usage.

According to O Reilly’s model, when all other factors are held constant, working in Europe or Asia seriously depresses earning power, by $24,000 and $3,000 respectively. Those toiling in the education sector took a hit of $30,036 for their trouble. Being female (only 15% of respondents were women) means you earn $17,294 less than your colleagues, an amount consistent with the gender gap as a whole and similar to the $17,318 toll that working at an early stage startup takes from a data professional’s paycheck.

To earn more, the model suggested moving to California (+$25,785), earning a doctorate (+$11,130), and learning how to use more data tools. Each new tool contributed up to $1,900 to salary. That adds up, as many respondents used up to 20 different tools.

Not all tools resulted in a similar salary boost, however. O’Reilly ran a clustering algorithm on the tools respondents reported that they used, and looked at the median salaries of those tool users. The median salary of Hadoop users, for example, was $118,000 versus $88,000 for those who don’t know Hadoop. Hadoop belonged to O’ Reilly’s Cluster 2 of tools related to the Hadoop ecosystem, including Elastic MapReduce, Cassandra, Spark, and MapR. Storm and Spark users earn the highest median salaries in the entire sample.

However, the most popular tools–used by 50% of data professionals–are the rather less glamorous workhorses of SQL, R, Python, and Excel. One entirely new tool cluster, Cluster 4, centered around Mac OS X, JavaScript, MySQL, and D3, also appeared for the first time in this year’s survey.

About the author

Lapsed software developer, tech journalist, wannabe data scientist. Ciara has a B.Sc.