Hiring data scientists: Cart before the horse?

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The most sought after skills in business today might be those practiced by data scientists. IBM claims there are more than 10,000 such jobs open if you search on Google. And the growing need for filling those jobs will lead to an acute shortage of people to fill those positions, according to a recent survey.

Data scientists have banded together online to help each other find work. They also have conferences to choose from to network with potential employers. However, at an upcoming event targeting data scientists, among the more than a dozen job titles encouraged to attend, one that's not mentioned is the chief data officer (CDO). That's a shame because data scientists should want to join businesses that value their data as a strategic asset, which means having a senior executive dedicated to exploiting that asset.

I've written and spoken about the critical need, especially in large enterprises, to create the role of a chief data officer. A CDO should oversee an array of IT responsibilities, including data integration, data management, business intelligence, predictive analytics, data standards, data governance, and more. In most large organizations those groups are managed by different people further down an organization chart, which can lead to battles over resources, such as which department gets to hire the much sought-after data scientist. This situation often leads to the most powerful group, not the most appropriate group, adding to its headcount.

Hiring data scientists without first having a clear leader in charge of an organization's overall data strategy strikes me as putting the cart before the horse. It also tells me that organizations hiring data scientists but lacking a CDO, even those companies drowning in data, continue to treat their information tactically. As such, they approach their data problem/opportunity in piecemeal fashion rather than holistically, putting their organizations at a competitive disadvantage and, in the long run, jeopardizing the newly minted data scientist's job. That is, without an overarching vision for an enterprise's data assets, data scientists likely will find themselves working in career-limiting stovepipe projects with less possibility of overall success for the business.

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