Beyond the Hype: Do You Really Need a Data Scientist?

Beyond the Hype: Do you need Really Need a Data Scientist?

In 2012, Harvard Business Review named data scientist as the “sexiest job of the 21st century,” and for good reason: They offer a unique combination of skills that neatly fit the needs of companies looking to leverage big data to make business decisions.

After all, these days, data sets aren’t always so simple. This is particularly true when it comes to big data, which is characterized both by the volume of information but also the variety of data sources involved. More skills are needed to wrangle data and connect it to business decisions.

This is where data scientists come in. Not only can they mine data from complex, large-scale data sources, they also have advanced statistical, predictive modeling and software engineering capabilities that allow them to turn a vague business idea into a data question, and then build out the methodology and tools to answer it.

What type of companies need one?

Job postings for “data scientist” increased at a mostly consistent (and dramatic) rate over the 2012-2016 period, including a period of intense growth in interest in June of 2013.

Do you really need a data scientist?

The hype of 2012-2013 may have seen its heyday, but in its place we see something even better: Solid demand and steadily rising job postings that demonstrate a maturing of the market.

Big data offers tremendous potential for things like understanding customers and buying patterns better and identifying potential efficiencies in processes (e.g. logistics). But too often, deep analysis of big data can’t be handled or managed well with existing technology. For companies with large amounts of unstructured data from varied sources, a data scientist can help bridge the gap by tying it to business decisions, goals and challenges.

For example, AT&T is one of the largest telecommunications company in the US. With hundreds of millions of wireless subscribers, they generate massive data sets. They use data scientists to dig into this data to learn about their customers and improve services, products and operations.

Companies with less complex data sets can probably skip the data scientist. A data analyst may be the better choice for these companies. They’re able to use existing analytic and business intelligence tools to interpret historical data and derive immediately actionable insights from relatively accessible data and information.

I need one—what obstacles do I face?

The good news is Indeed data show that interest from job seekers is also on the rise. In fact, analysis of jobs from Seen by Indeed, Indeed’s elite tech recruitment service, shows a relatively low mismatch between data scientist jobs postings and interested job seekers. Companies that need a data scientist now have more choices.

Share of clicks / Share of postings

But an increase in interest or data scientists doesn’t necessarily mean an increase in qualified applicants. It doesn’t guarantee companies will more easily find data scientists with the right mix of technology skills and business acumen for their particular goals and challenges – or even one that understands the nuance of their industry. This is still a rare combination of skills. Finding the best fit may still require some effort.

Data scientists are also very conscious of their worth and the competition for their talent. For instance, research from Indeed’s Hiring Lab shows that the average salary for data scientists is $117,000. Those with 10+ years of experience have an average salary of $137,500. Clearly, even with the hype dying down, data science is still a lucrative field.

In an already competitive market, where good data scientists go fast, companies on the hunt for great data science talent will have to step up their game to catch the cream of the crop. This means both knowing what to look for and being ready to offer competitive packages to fitting candidates.

How can companies do that? Aside from an attractive salary, new research from the Indeed Hiring Lab shows that today’s top performers want more flexibility and autonomy in their roles. Over half of the top 50 keywords associated with searches for flexible work are related to high-skill jobs, in fact. And in the US, the occupational category that gets the most interest from job seekers seeking flexible work arrangements is “Computer and Mathematical.”

Of course, finding top talent can be very complex and time consuming, especially in such a specialized field like data science. Seen by Indeed can help overcome these obstacles.

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