How To Win The Hiring War For Data Scientists

By one recent measure, the job market for computer and information scientists will grow 15% from 2012 to 2022, faster than the average for all other occupations. But according to separate research by McKinsey & Company, somewhere between 140,000 and 190,000 data science openings in the U.S. will go unfulfilled by 2018. Worse still, there will be some 1.5 million managers in the ranks of American businesses by then who lack the necessary backgrounds to put the available data to use.

These alarming shortfalls are tied to well-documented skills gap in science, technology, engineering, and mathematics (STEM) fields in the U.S today. If left unaddressed, the issue could hold back innovation and lower the productivity of entire industries. In short, American businesses are facing the prospect of being unable to understand the very data it takes to do business in the 21st century.

In response, many companies are ramping up their efforts at becoming more data-driven. As a result, a recruitment war in the data science field is now upon us. Companies will have to spend more per data scientist in order to attract the top talent. And those that can’t offer the most competitive salaries will need to find other enticements to offer. Here are four strategies for filling the data science knowledge gap in your organization.

1. Hire Early And Train Well.

A lot of great talent can come straight out of college. Look for recent or soon-to-be graduates with potential to learn and grow. With the right mentors and business environment, today’s data-savvy graduates can become tomorrow’s leading data scientists who are loyal to the companies that helped them grow, and that they themselves have shaped.

2. Adopt A Data-Based Culture.

A good data scientist can distinguish between a company that understands data science and one that merely practices data analysis. Those who don’t work in the field don’t always understand that data scientists just much more than analysis and reporting. A data scientist is part analyst and part artist—sifting through masses of information in order to spot trends, then making strategic recommendations based on them. Businesses that understand this difference have a recruitment advantage over those who lump all their data roles together.

3. Encourage Creative Approaches To Data.

It takes more than just creating the right roles for data scientists to really thrive in and improve a business, though. Companies need to encourage data scientists’ curiosity and creativity, empowering them to look into every area of the business. Nothing should be definitively off-limits. Letting data scientists explore and experiment only lets them sharpen their own skills, it also continually creates fresh opportunities to optimize the business. In a truly data-driven organization, the only limit to the sorts of problems data scientists can solve is their own imaginations.

4. Reward Great Work.

When your data scientists accomplish something big, show it—and them— off. Highlight the latest data-based solutions at company meetings. Encourage data science teams should to take part in industry events so they can showcase their work and learn new things. Not only will it help keep them abreast of the latest developments in the field, it will also give them a chance to implement new thinking in your own company.

The war for data scientists won’t be an easy fight to wage. Fortunately, technology is steadily lessening the data science burden for some companies in the meantime. Predictive analytics is steadily improving how marketing, sales, and other functions are done, and easy-to-use dashboards and machine-learning systems are helping make up some ground. With the right combination of these tools and diligent training, managers without data science backgrounds may be able to put data to better and more productive business uses.

But that still won’t reduce the need for bona fide data scientists, who are becoming more important than ever. Success in the digital world depends collecting, understanding, and acting on data-based insights. The companies that can’t will fall by the wayside.

Shashi Upadhyay, PhD, is CEO of Lattice Engines. Shashi is a Cornell University-trained data scientist and former McKinsey & Company partner turned entrepreneur who is now responsible for advancing Lattice’s vision to deliver the power of prediction to sales and marketing organizations.

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