Data leaders seek passion in prospective employees: Panel

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Big data; artificial intelligence; cloud computing; information security. The most important skill for a data professional to have on their resume this year is … passion.

Despite all the advances in and enthusiasm for hot and emerging technologies, what employers most need from analysts is a passion and enthusiasm for what the employee can do with data to drive business decisions and advance the corporate mission.

That was the key message to emerge from a roundtable on “Strategies for attracting, retaining and nurturing data analytics talent,” at the Chief Data & Analytics Officer Winter Conference in Miami last week. Leading the discussion were Pj Abhishek, senior vice president, revenue management and consumer analytics, at Wyndham Worldwide; Adam Michaels, senior director, forecasting insights and analytics, Mondelez international; and Elizabeth Farlow, director, operational analytics, Blue Cross Blue Shield of North Carolina.

The roundtable discussion, which included a dozen top level data analytics professionals or executives who manage data scientists, covered a number of topics related to best practices in recruiting data talent, which all agreed are hard to come by and increasingly expensive.

Nearly everyone agreed that it is impossible to find all the desired data talent needed in the workplace, especially as technologies advance so quickly. The best strategy is therefore to develop talent in-house whenever possible, and use a few very skilled data analysts as the “core” around which to build a team.

Abhishek compared the experience of staffing a data team to that of recruiting for the military. Pick a few seasoned data professionals that have the tech experience you need and a commitment to the cause, and use them as role models for the group. Then, hire lots of young data pros with mid or low-level experience, and let them learn from these champions. These low-level data professionals can be “easily molded,” Abhiskek explained, and they can hopefully buy-into the corporate mission quickly.

Farlow said her organization has also had success building teams around a few highly skilled data pros, but she cautioned that hiring at the entry level or low-levels of the data organization also brings challenges. For one thing, these hires lack “real-life data” experience. While these workers understand basic data science methods and technologies, they do not have the benefit of understanding what organizations actually do with data and how they can advance those efforts. That means lots of grooming will be required once the worker is placed into their job.

Once hired, the biggest challenge becomes getting a data analyst to see beyond their role to the big picture – what the organization is all about, who the customers are, how they are served, who the competition is, and how their individual role can help in advancing the organization.

“The biggest thing for my team is to be able to use data to drive for action and value – to affect change,” Michaels said.

The challenge of grooming young data professionals actually becomes a recruiting edge, Abhishek said. Data analysts want to view their work as important and part of a solution, so if the organization does a good job of explaining the role data plays in its success, that will help win over a candidate.

Beyond that, everyone in the roundtable discussion agreed that personality or “fit” was the most important standard for measuring a data analyst candidate. Technology skills can be easily taught to a technologist. Communication skills or so-called soft skills and are much harder to acquire.

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