4 careers where data science skills will help you get ahead

As the talent gap widens companies will likely require or at least encourage a certain level of data savvy from nontechnical team members to stay competitive in the market

 

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The need for data scientists is spreading across more and more industries. As companies in finance, insurance, and IT scramble to fill the role of data scientist, professionals in more traditional roles are encouraged to learn data science as well. It’s not just the looming talent gap that pushes individuals to learn data science; companies are using high salaries to woo people into the industry.
According to a 2014 Burtch Works study of salaries for data scientists, those responsible for a team of one to three people earned a median salary of $140,000. Those responsible for a team of ten or more earned a median salary of $232,500. To put that in perspective, the mean average annual income for a lawyer in the US was $131,990 and for a doctor $183,940.
McKinsey estimates there will be 4 million data-related jobs by 2018, as well as a shortage of 140,000 to 190,000 data scientists. These statistics mean that with an enormous talent gap, non-data scientists must learn data and analytical skills to fill the job gap.

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Current industries recruiting data scientists

As of now, the finance and insurance industries are pulling hard for more data scientists. 50 percent of all data science and data analytics job demand is from the finance, insurance, professional services, and IT businesses.

Big banks are competitively recruiting for data scientists as they realize the value of an employee that can manage predictive analytics and machine learning. The untapped potential of big data in banks is enormous, and the large firms have the cash to pay large salaries for staff that can help them stay competitive in the market.
While these industries are known for recruiting top talent, there is an increasing demand for professionals across many other industries to learn more about data science to stay relevant and enjoy job security.

The push for data education in new industries

According to IBM, the number of jobs for all data professionals in the US will increase by 364,000 openings to 2,720,000 by 2020. These industries are encouraging staff in the following roles to learn about big data and its power as they seek qualified data scientists.

Decision-makers

Though not an exact position, those executives that make big decisions should be data-savvy.  Data-driven organizations are 6 percent more profitable and 5 percent more productive than competitors. These numbers are likely to grow as the use of big data becomes more commonplace. Furthermore, in a study by Capgemini and EMC, 60 percent of respondents agreed that failing to use big data could lead to irrelevance and loss of competitiveness. Anyone in a leadership position, especially one that makes high-level decisions, should learn how to use big data and encourage employees to do the same.

Marketers

Marketers that can analyze data are at a considerable advantage and companies recognize this fully. According to Glassdoor, the median salary for job titles such as Marketing Technology Director and Director of Marketing Data is more than $150,000. Marketers that can handle large sets of data can make better decisions and use the data to predict consumer behavior—giving them a huge competitive advantage.
Using data-driven insights and proper analysis, companies can keep their existing marketing budget and see 10 to 30 percent higher performance on marketing initiatives. As marketers are pushed to show their worth through numbers, data-savvy individuals will have much more job security. Furthermore, because small and medium businesses may not be able to afford a data scientist, those companies are beginning to expect a level of data skills from incoming marketers.

Product managers

Companies seeking product managers are now including “analytics” and “data insight” on the list of desired qualifications. Businesses no longer need an intuitive product manager when they can hire one who makes data-driven decisions instead. According to business psychologist Tomas Chamorro-Premuzic:

Purely intuitive managers may face extinction only if they ignore the valuable information provided by data. At the same time, those managers who are capable of data-driven intuition will remain in demand, and increasingly so.

While product managers will still rely on customer feedback to create a robust product roadmap, data will play an equal part.
 

Human resources

A survey by IBM and MIT found that organizations that used HR analytics had “positive outcomes” on their business front and saw 8 percent overall increase in sales. The problem is that only 4 percent of companies have achieved the capability to perform predictive analytics on their workforce, which includes understanding what drives high performance and retention. The HR teams that did achieve success with data have much healthier leadership pipelines and are four times more likely to be respected by their business counterparts.
Data science can help HR teams to improve estimates on talent pools, acquisitions, cost-per-hire, cost-per-employee, and more. Harnessing the power of big data allows HR managers to forecast needs better as well.

Data education across multiple industries

One positive note is that marketers, product managers, HR team members, and decision-makers all have more access to learning about big data than they did before. With the surge in online courses and data science boot camps, almost anyone can learn this skill.
More and more organizations are realizing the skills shortage and therefore training internally to fill talent gaps within the company. At the same time, individual team members are realizing the career potential of having data science skills and are taking it upon themselves to learn more about this growing trend. As the talent gap widens, however, companies will likely require or at least encourage a certain level of data-savvy from nontechnical team members to stay competitive in the market.
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