Hailed by the Harvard Business Review as the "Sexiest job of the 21st Century" and by Glassdoor as the "Best Job of the Year" 2016. The role of the data Ssientist has been on the rise for some time and shows no sign of slowing down, as data becomes an increasingly valuable commodity to consumer facing businesses.

In fact, Dr. Andrew Chamberlain, Glassdoor's chief economist, described it as being “one of the hottest and fastest growing jobs we’re seeing right now”.

In 2017 we expect the demand will surge and with this, we are likely to see a broadening data skills gap and a serious shortage of good candidates.

The data science pool has always been relatively small and highly valued, with top level analysts often going into banking and actuaries. As more organisations build data science teams, it is clear the supply is not aligned to this increased demand.

The candidate pool becomes even smaller when you factor in interpretative capability. Whilst there are many that can analyse, there are very few that are able to use it to tell stories. Herein lies part of the problem; any role that is part science and part art usually presents a formidable task when it comes to finding the right person.

As an executive search practice we are being asked to hire increasing numbers of digital and data driven roles at director level. This is down to a general move towards “data based decision-making” and the requirement for top talent now reflects this.

In general, the challenge for hiring directors now, is to learn how to identify, attract and retain these candidates. It is not enough to rely on old methods to entice this most sought after group to join your business.

The following should be considered by C-suite and director level companies when looking to hire a data scientist:

  1. Clarity of Purpose 

Be clear about the role you are recruiting. Is this really a data science role? If so what does it include? What are the real responsibilities and accountabilities? As with any role it is crucial businesses have a clear definition of what this role looks like and where this role is in to the overall proposition.

  1. Have the right systems in place

There is nothing worse for a data scientist or technologist than not being given the right tools. The company must have invested or be prepared to invest in the systems needed to do the job and do it well and look at the bigger picture when considering making this sort of investment.

  1.  Provide intellectual stimulation

Organisations need to show that they will be a great host for a data scientist and enable them to grow and develop. Encourage them to bring new perspectives and innovative approaches to the table. Your data scientist must have the freedom they need to be able to look at old problems in new ways, discover patterns and to be able to challenge the conventional.

  1.  Be prepared to be challenged 

If you ask a question, be aware you might not like the answer. For the lateral data scientist the challenge of companies un-willing to listen to the ‘truth’ can be frustrating.

  1. Adapt your view of culture 

As with many technical roles, it may be necessary to think about the best ways to embed and retain highly intelligent and technical individuals and that may not meet the cultural norms of the organisation. Adjusting corporate culture to appeal to this group will end up being mutually-beneficial if done in the right way.

Whether you are recruiting yourself or using a specialist executive search company, you should expect to invest in the hiring process to get the outcome you want.

By Orlando Martins, CEO and Founder, ORESA Executive Search. The article was first published here