Businesses produce more than 2.5 quintillion bytes of data every day, according to IBM, and it’s up to a rising subset of workers to turn all that data into value.
Big data careers are hotter than ever, thanks to the influx of data from sources such as smart devices, e-commerce, and financial services. With more than 2.3 million job openings requesting analytics skills today, these professionals are in high demand.
Careers in big data fall into two categories: analytics-enabled jobs and data science jobs, according to professional services firm PricewaterhouseCoopers (PwC). The former category includes business executives, such as CEOs, directors of information technology, and financial managers, who need to know how to use analytics to make smarter decisions faster. These applications might include using data to identify customer needs, detecting unusual activity in real-time dashboards, or knowing how to forecast inventory using predictive analytics.
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The latter category is a burgeoning set of careers that stem from companies’ need to make sense of the mountains of data it’s collecting. These big data careers are the most analytical roles in the market and require people skilled in programming and applied science, who are proficient with large ranges of specialized analytical skills and tools, such as data visualization and analysis, Hadoop, R, and Tableau, according to IBM.
Data analytics professionals are in high demand across industries—from healthcare and city government to higher education and marketing. Finding qualified individuals to fill these rolls, however, hasn’t been easy. These data science jobs require candidates with both experience and advanced degrees, who have expert analytical, technical, problem-solving, communication, creativity, and teamwork skills.
According to IBM, job openings for data scientists—the fastest-growing career in data analytics—will reach 61,799 by 2020. While this is a significant number, it still represents just two percent of the projected demand across all jobs requiring data and analytics skills.
Today, a handful of new careers in big data are emerging, thanks to businesses’ evolving analytical needs. Here’s a look at what those roles are and the functions they fill.
1) Citizen Data Scientist
Research and advisory company Gartner discusses the growing importance of the citizen data scientist—people on the business side who “create or generate models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.”
Gartner predicts that citizen data scientists will surpass data scientists in the amount of advanced analysis they produce by 2019.
2) E-Discovery Investigators
Robert Half Technology named e-discovery investigators one of the top emerging tech jobs. These professionals specialize in uncovering, collecting, and analyzing data from connected devices. They might examine phone logs or pick apart instant message transmissions—any digital footprints a criminal might leave behind—which could lead to the scene of a crime.
3) Data Analyst
Data analysts are responsible for helping companies make sense of their large volumes of data. Sometimes referred to as a “business analyst,” the need for these professionals is increasing: The U.S. Bureau of Labor Statistics projects the field to grow 19 percent from 2014 to 2024—much faster than the average for all occupations.
4) Machine Learning Specialist
Machine learning specialists are similar to data analysts in many ways, but the key distinction is their end goal. As a data analyst, your analysis is performed and presented to those who make business decisions. Machine learning specialists, on the other hand, produce software that runs autonomously. These professionals are valued for their expertise in areas such as data structures, computer architecture, and system design.
Postings for these jobs have been steadily increasing since 2014, according to a recent report from Indeed.
5) Big Data Engineer
Big data engineers turn vast amounts of data into insights that can be used to inform a company’s decision-making process and overall strategy. The role requires knowing how to collect, interpret, and report on an organization’s data, according to Robert Half Technology—data that often needs to be pulled from a variety of sources.
The growth of this position has outpaced that of data scientists, according to technology jobs site Dice. The site describes the need by saying:
Data engineers build and maintain the pipelines that keep your data clean and flowing. Insights are great and you need them. But to deliver insights at scale, you need data infrastructure.