What You Need to Consider When Hiring a Data Scientist

Dubbed “the sexiest job of the 21st century” by the Harvard Business Review, the demand for data scientists has grown dramatically. The number of job postings for this career increased by 31% from December 2017 to December 2018. And over the course of the last 6½ years, postings have surged by a staggering 256%. 

Given the impact a data scientist can have on a company, many businesses are looking to hire one of these professionals. If this sounds like you, here’s what you need to consider when hiring a data scientist. 

Competition

First of all, be aware that a lot of companies are competing to find top data scientists. According to PricewaterhouseCoopers (PwC), there were 2.3 million open jobs seeking analytics skills in 2015, but that number jumped to 2.9 million in 2018. The demand is especially big in larger markets like New York, California, and Texas. 

So there’s a good chance you’ll face some stiff competition with your search. Because of this fact, PwC says most companies look for candidates with analytics skills rather than specifically seeking analysts. According to PwC, “Common analytics-enabled jobs are Chief Executive Officer, Chief Data Officer, Director of IT, Human Resources Manager, Financial Manager and Marketing Manager."

HackerEarth says talented individuals should have skills in three main fields: mathematics and statistics, machine learning and programming, and business/domain knowledge. It's important to remain flexible when hiring a data scientist, and you may need to look for candidates that possess a variety of skills.

Understanding Data Science – Venn Diagram

It’s also helpful when you have a basic understanding of data science and the core elements that go into it. Perhaps the best way to gain that understanding is to look at this simple illustration of a Venn Diagram from one of America’s premier data scientists, Drew Conway. 

As you can see, hacking skills, math and statistics knowledge, and substantive expertise are the primary colors. Having a mix of these disciplines and experience is essential in this industry and something any qualified candidate will possess. 

When you look deeper at the secondary colors, you see the skills that arise when the primary colors overlap, with data science being right in the middle. Note that the “danger zone” refers to data scientists who have significant hacking skills and expertise but may lack the ethics or knowledge to properly apply them.

How to Find and Hire Data Scientists

When it comes to acquiring the best and brightest data scientists, here are four helpful tips:

1. Define your company’s specific needs. Think about your unique challenges and figure out which aspects of data science are most important. 
2. Consider hiring internally. In many cases, existing employees can pan out better than external hires because of their knowledge of your business and customers. 
3. Look for quick learners who are creative. Getting acclimated to your industry takes time. Finding someone who can rapidly adapt and think outside the box is a huge help. 
4. Look for candidates with consulting skills. This is important for talking with customers and coming up with effective solutions. 

It’s also smart to look for someone who’s well-versed in web data integration – a process that aggregates data from alternative web sources and enhances its quality. “IBM estimates that poor-quality data costs businesses in the U.S. more than $3 trillion annually,” says Gary Read, CEO of Import.io. “An end-to-end web data integration strategy is game-changing for those serving the financial sector, e-commerce or other data-driven businesses.”

Conclusion

With 2.5 quintillion bytes of data generated every single day, modern businesses need a way to make sense of it all. Hiring a data scientist allows you to do just that, and can greatly improve your organization’s decision-making. Knowing the competition you’re up against and which specific skills to look for in a candidate should ensure you make the right hire. 

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