One 2019 report from Indeed indicated a 344% rise in the demand for data science specialists since 2013 and a 29% year-over-year increase.
Bureau of Labor Statistics expects the operations research analysis and computer research information science fields to grow by 27% and 19%, respectively, by 2026, which they deem “much faster than average” growth.
Other job websites corroborate these numbers and note that it isn’t just tech companies looking for data scientists — job listings span the gamut of industries.
With good reason, too.
Data is the new oil, as they say — and it powers every corner of commerce and human enterprise.
Big Data Is Big Business (And Big Opportunity) For job-seekers everywhere, the implications are clear — if you have a head for numbers and an eye for detail, then big data and data science could be extremely lucrative and stable career tracks.
The fact is, big data has become a competitive advantage among companies in virtually every industry, from health care to logistics to supply chain management to merchandising analysis to marketing campaigns.
Data fuels companies large and small and keeps them fed with historical and real-time insights upon which to build business decisions, launch newer and more personalized products, engage in expansions and acquisitions, fine-tune outreach and marketing, and much more.
But the problem, according to Michael Chui of the McKinsey Institute, is that “it’s super hard to find the right talent.
” Moreover, this lack of talent results in companies not fully understanding the opportunities that big data represents in the first place, such as clearer customer insights and leaner operations.
In other words, it’s a catch-22 — we need more big data expertise to prove the value of big data expertise.
Nevertheless, the word is getting out.
Data science is “sexy” now, and smaller and mid-sized companies are adding their own slate of job listings alongside big names like Google, Microsoft and Apple.
And the arms race for big data talent has placed such professionals in an incredible position to market themselves and find a company and career path that truly suits them.
So the question becomes — What’s the best way to close this talent gap and connect employers with qualified and motivated candidates?.How to Cultivate Big Data Talent In a report called “The Quant Crunch,” IBM lays out the scope of the problem and provides several ways industry and educational entities can marshal their forces to address the impending shortage of qualified DSA job applicants.
First up is the challenge of communicating to K-12 students, college students and those looking for new opportunities.
Since data science is everywhere, these jobs are everywhere too.
IBM identified the following industries as those with the highest demand for DSA talent.
The percentages express the proportion of company job openings which fall into the DSA category: Finance and Insurance: 19%Professional, Scientific, and Technical Services: 18%Information services: 17%Management of Companies and Enterprises: 13%Manufacturing: 12%Utilities: 10%Wholesale Trade: 9%Mining, Quarrying, and Oil and Gas Extraction: 9%Public Administration: 7% From insurance to scientific research to retail to public service, there isn’t a single industry that isn’t being disrupted by this shift in the job market.
Moreover, notes IBM, the human race generates 2.
5 quintillion bytes of data daily.
Netflix is ostensibly an entertainment company, but every decision they make relies on the apparent mountain of user data they sit on.
Uber isn’t a transportation company — they are, in the words of their leaders, a technology company.
We’re looking at a whole new kind of economy here.
So how can we prepare people for it?.IBM has some ideas on that front: Start Data Literacy Education Early: Organizations realize the benefits of adding big data talent to their value chain.
But the general public might be lagging behind.
IBM recommends adding “baseline data literacy” to our educational institutions as early as junior high.
Doing so would prepare graduates with a firm understanding of the basics and ready them for additional, more finely-tuned training in an industry that appeals to them.
More Focus on DSA Skills in Higher Learning: Higher learning institutions must, in turn, add new courses and degree tracks to their offerings — many already doing so.
IBM observes that 42% of open data scientist positions require candidates with a graduate degree and 20% of positions require at least six years of hands-on experience.
We need more colleges with classroom experiences and internship opportunities specifically tailored to big data.
Lower Hiring Requirements: Recognizing the value of driven and self-motivated problem-solvers, some major employers like Microsoft and Hasbro, are lowering their experience and education requirements for job applicants or splitting existing roles which had such requirements into multiple entry-level positions which do not.
Of course, even these recommendations aren’t enough — not when technology skills in general, and DSA skills specifically, change so regularly.
eLearning has long been seen by many as one of the remedies for a rapidly changing economy and the emergence of brand-new disciplines.
We already see an explosion in eLearning options for students even in K-12 schools.
This could help school districts more finely tune their course offerings, cast a wider net for high-quality educators and experiences, and stay more agile as the needs of the job market change further.
The importance of big data expertise couldn’t be more clear — for companies or for job-seekers.
Thankfully, a more complete picture is emerging for how we can prepare many more people for a role in this exciting and quickly growing field.
About the Author Contributed by: Kayla Matthews, a technology writer and blogger covering big data topics for websites like Productivity Bytes, CloudTweaks, SandHill and VMblog.
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