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Why data scientist is the hottest tech job in retail

Sharon Goldman | April 14, 2016
It should be clear to every IT leader in every industry that data is eating the world. The retail sector is no different. And finding the people who can mine the gold out of the vast veins of data running through the retail world is proving particularly challenging.

Depending on the retailer, there is also the challenge of unwinding the existing IT infrastructure, points out Joseph Madigan, senior director and retail practice lead at management consulting firm SSA & Company. “Retailers need data experts who can unwind old legacy pieces and get new systems ready to launch on a foundational platform that moves towards omnichannel.” 

One big reason data scientists are so hard to hire is that there are two roles the retailers need — data engineer and data scientist — and most companies try to pack them into one job, says Jonathan Beckhardt, founder of DataScience, which offers retailers and other companies an outsourcing option. 

“The data engineer gathers and collects the data, but the data scientist is the one that then extracts value from that data and tries to understanding the meaning and signals in the data,” Beckhardt says. “A few years ago everyone started tagging all of their data, and now have fantastic volumes of it and it’s hard to manage it all. You need both skillsets but companies are trying to find those things in one person.” 

But even for companies who understand the different roles — and who has found someone with a really rigorous understanding of math and statistics, probability and domain expertise — they still might not be able to hone in on the perfect candidate. “That’s because of the soft skills you need, too — communication, critical thinking and persistence to push through challenging problems,” he says. 

Recruitment strategies for retailers 

To attract the best data science talent, retailers need to build a unique digital and analytics brand, as well as use cross-disciplinary teams to embed analytics throughout the organization, and build industry-university partnership to tap into talent, says Christian Hagen, partner at global management consulting firm A.T. Kearney. The company’s 2015 Leadership Excellence in Analytics Practices study found that leading firms are much less likely than laggards to hire experienced professionals, opting instead to build from within or grab talent straight out of college. 

“Given enough time to grow, these junior hires can be taught the specific skills necessary for their company’s business and industry and be just as valuable over the long term,” he says. 

But overall, retailers cannot expect to be experts across all of the data that is potentially available to mine for greater sales, says Redd. So, to attract data science talent, an element can be as simple as creating a “Center of Excellence” within a retail enterprise, as well as a place that houses the data scientists. “When a data scientist builds a compelling analysis, it should be done in a way that it can be shared with others throughout the organization so if that person leaves, it can be picked up by others,” he explains. “It also creates an appeal to data scientists by showing how committed the company is to their skill set.” 

 

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