Predictions for the 2016 Big Data Hiring Market

An Chair in the server room .

Over the past two years, when I’ve set out to write my predictions list, each post began the same way: the hiring market for analytics professionals and data scientists was hot last year, but this year it will be on fire! I’d start this year’s post off the same way, but it may start to sound like a broken record – except that it’s true! Chances are, if you’re reading this post, I probably don’t have to elaborate further on just how great this demand is.

This immense disparity between supply and demand, plus the rapid evolution of the discipline, has had interesting effects on the hiring market thus far, and this year will be no different. Here are some trends to watch out for:

1. Quants, quants, everywhere! – Almost all companies are now aware that data-driven decision making is critical if they want to succeed. Many are still trying to staff with the talent shortage in full force, and I expect to see even more teams getting on board this year as they hurry to catch up to the rest of the market.

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2. Educational backgrounds continue to diversify – Newer MOOCs, bootcamps, certifications, and freshly minted Master’s programs are becoming ubiquitous, with even more popping up so frequently that it is difficult to find an up-to-date list of all the programs available. Now that some have been around long enough to graduate multiple cohorts, we can start to get a sense for which programs are stronger than others, and there will be a shakeout. As these fresh graduates come onto the market, some will be better trained than others, so it will be important to carefully evaluate their skills and understand that there is a huge disparity in quality.

3. Companies compete for experienced professionals – Thanks to all of the new educational programs and all of the students flocking to analytics and data science there are increasing numbers of inexperienced quantitative professionals out there. However, hiring groups are generally most interested in candidates that have at least some business experience, preferably in a specific domain, so that they can guide more junior team members. But, the pool of people with 4+ years’ experience is slim relative to the demand, so if you’re looking for someone with more experience it will be difficult.

4. FANG, aka Facebook, Apple, Netflix, Google (et. al.) are aging – Just like all of us, the big tech companies are indeed getting older. While these companies will still attract some of the best and brightest talent, they are becoming less agile and more process-bound. In the past, many professionals would never even consider leaving jobs at those companies, but that has been changing as some have left in favor of startups in search of “the next big thing”. I have even heard that fresh grads from the top programs are turning up their noses at Facebook! Just as FANG is getting long in the tooth, perhaps some of the unicorns are losing their horns also.

5. Open source tsunami! – Last year, open source software gained some serious traction because of Apple, Google, Elon Musk, and more. This year, I predict that R and Python will overtake SAS in popularity among analytics professionals and data scientists. The number of quantitative professionals who preferred R in our SAS vs. R survey increased from 35% in 2014 to 48% in 2015, and so I’m anxious to see what this year’s results show.

6. Data Scientist title continues to be abused – Perhaps it’s confusion about the term, or perhaps it’s wanting to jump on the bandwagon (or maybe a little bit of both), but misuse of the “data scientist” title reached epic proportions last year (for the record, this is how we define a data scientist). Since it’s unlikely that this issue will correct itself anytime soon, make sure to vet whoever you’re hiring based on their skills, not just their title. On the flip side, if you’re a hiring manager, make sure to evaluate whether the position you’re hiring for is truly data science – or is it a marketing scientist, web analyst, or a business analyst?

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7. New applications for data analysis will spring up – Sure, all the usual suspects will continue to hire (retail, advertising, tech, insurance, entertainment, etc.), but this year look out for more quantitative hiring in less-established areas like healthcare, fin tech, and transportation.

8. Consulting hits a speed bump – Smaller boutiques and legacy firms alike did not have the best year in 2015. I am hearing about pivoting, rightsizing, and bench-sitting, and that will likely continue into this year.

9. Salaries rise again – Salaries will continue to go up for this in-demand group. Wait, that’s not so much a prediction as it is a foregone conclusion, right?

What do you think, will this be another record-setting year for Big Data? Or will this be the year that the hype begins to taper off?

To learn more about The Burtch Works Studies, which are salary reports for professionals working in Marketing Research, Predictive Analytics, and Data Science, or to download them for free, click here.

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This article was written by Linda Burtch from Business2Community and was legally licensed through the NewsCred publisher network.

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