November 16, 2015
These days, it’s all about data. Businesses want more information so they can make smarter decisions. For sales teams, having this information could be the difference between closing a deal or losing a sale.
Despite the prominence of Big Data in every business, a recent estimate from McKinsey found there will be a gap of between 140,000 to 190,000 people with requisite analytical expertise in the American economy by 2018. It’s clear that businesses need these qualified professionals in order to unlock the power that big data holds, but finding and hiring those candidates is a different story.
The right candidates are out there. You just need to change where and how you look for them. Here are three tips for ways to find the right data scientists to help your company turn big data initiatives into real business value:
Understand What You Need
Before any investment, you need to identify which analytics will be the most useful in helping you to achieve your goals. “Data scientist” is a broad stroke. Some businesses need to analyze machine data. Others need to analyze human behavioral data. If your company wants to improve ad targeting capability or recommendation engines, your ideal candidate needs a background in mathematics and computer science.
Whereas companies that need to piece data from product performance and customer sentiment into a narrative can find strong candidates from advanced social science fields. Professionals with training economics, sociology and other similar fields are adept storytellers. These kinds of data scientists are skilled at piecing together ambiguous data points into meaningful conclusions. When you spend the time to truly understand what you’re looking for, you’ll realize there are more quality candidates available for hire.
Hire for Talent, Teach the Tech
In a perfect world, every candidate would have extensive training and certification in using Sequel, R, Python or any other sophisticated analytics engine. That’s just not the case, though. The supply shortfall gives companies willing to teach and train hires on technology a big advantage.
Analytical thinking and a background in pulling analytics from data are far more valuable than the ability to use a specific kind of software. You can’t teach people to think a certain way, either. Data scientists are frequently highly analytical thinkers whose logic helps them weave together simple narratives from complex, disparate data points. No matter how well a candidate knows a piece of software, they can’t help your company if they’re incapable of reasoning.
Additionally, training programs that help fledgling data scientists learn your company’s preferred technology provide great opportunity for team building and mentorship. When people work closely together and collaborate to learn from each other, they become more cohesive teams.
Look Outside the Box for Candidates
The existing talent gap is an opportunity for you to identify candidates from nontraditional analytics backgrounds. Technology companies can – and usually do – hire the best and brightest from some of the world’s foremost universities. However, expanding your candidate pool can uncover qualified professionals who may not have considered a career in data science.
Aside from the obvious need created by demand and underwhelming supply, looking outside the box for candidates can result in more diverse data science teams. Whether it’s gender, race, age or background, teams of all sorts benefit from diversity. When your team is made up of professionals with different educations and from varying backgrounds, it has different perspectives that can help in problem solving. Diverse thinking also improves innovation and eventual opportunities to expand revenue.
The insufficient talent pool for data science has also resulted in the emergence of nontraditional educational programs specifically designed to prepare people for careers in the field. Actively recruiting from these kinds of programs is a chance for your company to attract more people and find the best candidates to address challenges in data science.
More and more companies are finding that a data scientist will help to take their business to the next level. However, not every company can recruit exclusively from the best universities to attract the right candidates or hire a seasoned professional with no training needs. It’s not necessary that you do either. A data scientist can come from any number of educational or career backgrounds and add substantial value to your company. With hundreds of thousands of data science openings going unfilled, business owners must adjust the way they approach recruitment to find untapped talent.
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