Finding talented data scientists is no easy task. In fact, a recent Information Management article by Dermot O’Connor, cofounder of the cloud provider Boxever, called good data scientists “unicorns” because “it is so rare to find professionals who possess all the right skills to meet today’s requirements.”

The challenge is likely to become even tougher with time. Boxever, in his article, cited an observation made by management consulting firm McKinsey that the U.S. may face a 50 percent to 60 percent gap between the supply and demand of analytic talent as soon as next year.

And, with so many companies recruiting data scientists, it’s imperative that we start working now to attract the next generation of talent into data science and other tech occupations.

But how do you even spot someone who might have what it takes? What makes a great data scientist?

Let me list a few attributes. A data scientist is someone who:

Thinks “Strategy First.” The first definition of “strategy” is a “plan of action or policy designed to achieve a major or overall aim.” Technologists favor strategies before tactics – i.e., actions and activities implemented to achieve an objective. Rather than a reflection of values, this intellectual sequence is a simple acknowledgement of the way most technologists – and data scientists – are wired. Before they start working with technology or put technology to work, technologists step back and plan. So do the best data scientists.

Has a passion for solving problems. Technologists don’t see problems as obstacles to avoid; they consider problems opportunities for solutions. Their innate curiosity leads them to confront challenges even when they are not obvious. And their willingness to take initiative drives them to explore ideas, options and scenarios as a means of identifying and designing constructive solutions. This is the same reason the best data scientists don’t create analytics for questions that don’t need answers.

Sees technology in a constructive context. Technologists appreciate that, in the broadest sense, technology is a tool whose value is determined by its application for the benefit and assistance of people – whether in their personal or professional lives. The best data scientists know the same can be said of analytics in their many forms.

Believes tech is about humans, not hardware. Technologists see gadgetry as solutions that serve people. No gadget has value unless it helps a customer, colleague, citizen, patient or any other type of person a technologist may encounter during a career. Technologists believe the measure of a job well done is the benefit the technology solution brings the people who experienced the problem. So, the best data scientists concentrate not only on developing analytics, but on helping people visualize information.

Values respect, cooperation and collaboration.
Technologists maintain a positive, helpful disposition on the job and in relationships in or out of the workplace. They respect their employers’ codes of conduct, appreciate the contributions of colleagues and understand that going rogue isn’t the best way to analyze a problem, execute a strategy or implement a solution in a business context. This is the reason a technologist’s standards of behavior do not tolerate racism, sexism, ageism or any other approach that demeans others inside or outside an organization. The best data scientists do the same, because to do otherwise would be to ignore or dismiss the insights they worked so diligently to deliver.

Who is inspiring the young people of today to be technologists of tomorrow? CompTIA’s NextUp initiative, which is managed by Creating IT Futures, is partnering with three programs targeting middle-school students in the U.S.:

· TechGirlz, workshops for middle-school age girls;

· FUSE, a school-based series of tech-related challenges developed by Northwestern University;

· And, Hack Your Health workshops, developed by the New York Academy of Sciences (NYAS).

These efforts and others like them will help create a generation of technologists who not only understand how analytics function, but who help bring to realization a data science industry that works, competes and innovates for decades to come.