Data Science Skills To Boost Your Salary

Data Science Skills To Boost Your Salary

Are you a data scientist wondering how your compensation stacks up to your peers? Or are you considering a career shift to data science? Here’s a look at how much you can expect to earn.

(Image: penguiiin/iStockphoto)

Data scientist may be the hottest job title in the IT and overall technology space right now. The number of data scientists has doubled in the last four years, according to a recent study of LinkedIn profiles performed by cloud analytics firm RJMetrics. Career site Glassdoor recently ranked data scientist as No. 1 on a list of top jobs that offer the best work-life balance. (You can see the rest of the list here.)

On Oct. 20, Glassdoor reported that it had 1,315 listings for data scientist job openings. According to Glassdoor, data scientists can expect a salary of about $115,000.

[Looking for more on skills to boost your career? Read 10 Skills CIOs Need to Survive, Thrive in 2016.]

So, if you are considering adding data science or analytics skills to your resume, you may find your value in the IT jobs market increase. If you are thinking about making a full career switch, you will be joining a small but fast-growing profession.

O’Reilly, which runs the Strata+Hadoop events, recently provided some additional data points for those considering a career in data science. The company published its third annual Data Science Salary Survey. The report covers compensation and also looks at trends in tools and job tasks for those in the data science field.

To compile the O’Reilly report, the authors used an online survey to collect information from more than 600 respondents who ran the gamut of job titles. Only about one-quarter of the participants had a job title that explicitly identified them as data scientists.

Others went by titles that included analyst, engineer, developer, architect, business intelligence professional, and statistician. Executives and management were also represented in the survey. Other participants were students, consultants, and professors. About two-thirds of those who participated are based in the US.

O’Reilly’s authors ran several different models, as data scientists do, to look at the results in different ways. What follows are the results from a few different models, but we mostly used the results from the final model. This model excludes those who self-identified as upper management from some of the analysis, and also controlled for other factors. We recommend readingthe full version of the report for more information.

O’Reilly notes that understanding salary is tricky:

Statistics from an anonymous online survey based on a self-selected sample doesn’t exactly put the “science” into “data science,” but such research can still be valuable — and let’s face it, much of the other information that might inform one’s understanding of industry trends is in the same assumption-violating category.

Want to make this survey better? O’Reilly encourages data scientists to take the current survey. You can find it here.

But before you do that, take a look at the compensation, tools, and trends for data scientists in 2015. Once you’ve reviewed these findings, tell us what you think in the comments section below.

Are you currently working in a data science role? Does your compensation stack up? If you’re not currently working in a data science-related position, is it something you’re considering adding to your skill set in the year ahead?

**New deadline of Dec. 18, 2015** Be a part of the prestigious InformationWeek Elite 100! Time is running out to submit your company’s application by Dec. 18, 2015. Go to our 2016 registration page: InformationWeek’s Elite 100 list for 2016.


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