The Quant CrunchHow the Demand for Data Science Skills is Disrupting the Job Market
“Hybrid jobs” are projected to grow twice as fast as the rest of the job market.
In Singapore computer science skills, but not necessarily computer science degrees, are increasingly in demand by employers.
Data Science and Analytics are no longer just buzzwords–they are essential business tools. As new technologies and methods make a dent in the economy, so too are they making a dent in the data science job market. In this report conducted for IBM and the Business-Higher Education Forum, Burning Glass Technologies made a comprehensive study of the marketplace for data science and analytics skills. We found the data science job market is growing rapidly, and that the demand is having a particularly strong impact in decision-making roles.
- In 2015, there were 2,352,681 job listings for all DSA categories. The demand for DSA jobs is projected to grow by 15% over the next five years, which translates to nearly 364,000 new job postings expected nationally by 2020.
- The fastest-growing roles are Data Scientists and Advanced Analysts, which are projected to see demand spike by 28% by 2020. This category and Analytics Managers are arguably the most visible categories in the data science job market, yet they are also the least demanded in terms of total job postings.
- DSA jobs remain open for 45 days— five days longer than the market average.
- The difficulty employers have filling DSA roles drives up salaries, and relative to other jobs, DSA jobs pay quite well. On average, they advertise an annual salary of $80,265—a premium of $8,736 relative to all bachelor’s and graduate-level jobs. Some DSA jobs, such as Data Scientists and Data Engineers, demand salaries well over $100,000. While this is encouraging for prospective DSA workers, this makes it costly for employers to fill open roles.
- Compounding the skill shortage is the hybrid nature of many DSA jobs, which require a mix of disparate analytical skills and domain-specific expertise that may be difficult to develop in traditional training programs. Marketing Analytics Managers, for example, must combine advanced analytical techniques with deep marketing knowledge, but both skillsets may take years to develop.
As demand for DSA workers grows, this growth puts pressure on the supply of DSA talent to grow in turn. To mitigate this talent shortage, organizations across the analytics ecosystem must build a detailed understanding of their talent needs. This will enable them to invest strategically in DSA talent pipeline development. Similarly, educators and training providers must respond to the rising demand for analytics skills with programs that prepare students for the analytics-related roles of today and tomorrow, while existing workers must continuously monitor in-demand analytics technologies and update their skillsets accordingly. If these actions are not taken, the DSA skills gap is in danger of widening, which would continue to undercut the promise of Big Data.