Data Science Skills To Boost Your Salary - InformationWeek

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11/17/2015
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Jessica Davis
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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.
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(Image: penguiiin/iStockphoto)

(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 reading the 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.

Jessica Davis has spent a career covering the intersection of business and technology at titles including IDG's Infoworld, Ziff Davis Enterprise's eWeek and Channel Insider, and Penton Technology's MSPmentor. She's passionate about the practical use of business intelligence, ... View Full Bio

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jries921
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jries921,
User Rank: Ninja
11/23/2015 | 6:08:33 PM
Re: More Meetings = More Money
Another possibility is that as one acquires supervisory responsibilities, he finds himself in more meetings whether he wants them or not; and as he gains more seniority, he finds himself more frequently in direct contact with consulting clients.  I doubt that participation in meetings per se increases one's earning capacity.

In short, More Money = More Meetings, not the other way around (the commutative property doesn't work in this case).
nomii
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nomii,
User Rank: Ninja
11/23/2015 | 12:27:58 PM
Re: Negotiation Skills

@Shamika the tech is very dynamic in nature and is changing every instant. I am sure that by the time someone is skilled in the job of Data science, it must have opened a new venture or new skill. I think we need to initially get ourself accustomed to the basic requirement of the job and then we can have specialized fields. I think this way it will be far easier to adopt or change with the changing envirnoment. I field of IT being stagnant means yu are dead. What do you say?

jagibbons
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jagibbons,
User Rank: Ninja
11/23/2015 | 10:14:47 AM
Re: Working long hours:
Much like the fact that good negotiation skills help drive higher salaries in any industry or specialty, I'm thinking that working more hours helps in any position as well. Salary is driven by a number of factors, one of the key factors being the value the employer places on you. Up to a point, working more hours (productive hours actually delivering value) will increase that part of your personal value proposition.
jagibbons
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jagibbons,
User Rank: Ninja
11/23/2015 | 10:10:20 AM
More Meetings = More Money
Interesting about the correlation between meetings and salary. Data science is still probably a lot more art that science, so it's critical to be seen doing the role and contributing to the company's success. It makes sense that if you are seen doing that role, if you are making a noticable difference to the bottom line through data science, your salary will grow as you are recognized for those contributions.
Gigi3
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Gigi3,
User Rank: Ninja
11/23/2015 | 2:19:37 AM
Re: Valuable Insights on the Skills
"Agree that data science is hot in the technology space right now.  I enjoyed learning Spark & Scala myself this year."

Jules, so you are already equipped with necessary skills. Did you find anything (job/career) in a useful way with this new skills/tools.
Gigi3
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Gigi3,
User Rank: Ninja
11/23/2015 | 2:15:53 AM
Re: Career opportunities with Big Data
"I agree with you. This is new domain for IT professionals. However,  I not sure whether we have categorized the correct skills and expertise that we should look for."

Shamika, as of now it's taken care by normal data/analytical peoples. But if we need to use it efficiently, specially skilled peoples are very much required. 
julesagomes
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julesagomes,
User Rank: Apprentice
11/20/2015 | 4:15:19 AM
Valuable Insights on the Skills
Agree that data science is hot in the technology space right now.  I enjoyed learning Spark & Scala myself this year.
TerryB
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TerryB,
User Rank: Ninja
11/18/2015 | 12:57:41 PM
Re: Excel: 59% of respondents
You mean just the sheer skills needed to mine terabytes and terabytes of raw data? I guess that makes sense as an IT type job, you won't learn that in Calculus or studying probability theory. Thanks for clarifying.
jyalai
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jyalai,
User Rank: Apprentice
11/18/2015 | 12:50:19 PM
Re: Excel: 59% of respondents
I assume the term data science refers to the highly technical nature of data manipulation that, many times, falls into the business analyst's role.  When it comes to data manipulation, my experience is that Excel is still the most predominant tool used among non-IT business analysts, while more IT focused roles using data science use SQL.
TerryB
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TerryB,
User Rank: Ninja
11/18/2015 | 12:37:53 PM
Re: Excel: 59% of respondents
I must be missing something here on this job title? Why is working with data in Excel considered an IT job and not just a business user job? We've always had Business Analysts or Programmer/Analysts but that historically meant you focused on the business requirements needed in an IT application to be developed.

What you are describing sounds like something that belongs in the Marketing realm? Or engineering if the data collected is related to machine health.

That doesn't change basic point here that it seems to be a hot job now. Just wouldn't necessarily think it would take a degree in Computer Science to do this. Math, definitely. Statistics, definitely. Traditional Comp Sci, not sure about that.
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