Why data scientist is the hottest tech job in retail

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.

How to Break Into Data Science
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They have been called “unicorns,” because they are so hard to find. Their position has been called the “sexiest job of the 21th century.” They are data scientists, a job which – in a world where big data now permeates every industry and requires the right people to extract knowledge and insights – not surprisingly topped Glassdoor’s list for the 25 Best Jobs in America for 2016. 

These hires are critical, say experts. “It’s essential for not only collecting, managing and analyzing supply chain data, but also for garnering advanced predictive analytics to help executives make more intuitive, accurate and reliable, allowing them to deliver goods and services ahead of the competition,” says Richard Howells, global vice president of extended supply chain at SAP. “It’s all about keeping up with the latest consumer trends and demands and ensuring that you have the right products, in the right place, at the right time to meet those demands.” 

Retailers are searching high and low for these data “geeks,” but the industry is far from alone in experiencing a shortfall. McKinsey projects there will be a 40-60 percent shortage of qualified applicants for these positions by 2018. However, retail has particular difficulty hiring for these positions for two reasons, says Tom Redd, global vice president of strategic communications at SAP Retail. “One is because most people do not think of retailers analyzing this data. Most people assume that retailers outsource the data analysis so they are not the ones doing the hiring,” he says. “The other one is that universities are just now gearing up to develop programs addressing this issue.” 

Retailers require rare data skills mix 

In today’s consumer-focused retail universe, which demands an increasing level of personalization and relevance, every retailer needs to understand shoppers through the use of data. According to Steven Skinner, senior vice president at Cognizant Business Consulting, Products and Resources Practice Leader, the reason data scientists are so difficult to find in retail is because of the rare mix of business acumen, technology skills, intuition, and math they need to bring to the role. 

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“Retailers need to create curated, synchronized, relevant, and simplified customer engagement at every touch point in real time,” he says. “This means the underlying analytics are imperative to meeting that goal of increased customer relevance, reduced customer churn, and higher basket sizes, as well as assortments that are locally relevant.” 

Harnessing all of data and turning it into actionable information requires a specific skillset and expertise that hasn’t been required until now, adds Howells. “You need to understand how to analyze the data, but also the business processes and needs,” he says. “This person is critical for not only collecting, managing and analyzing supply chain data, but also for garnering advanced predictive analytics to help executives make more intuitive, accurate and reliable, allowing them to deliver goods and services ahead of the competition.” 

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. 

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“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.” 

In general, retailers need to create a learning innovation environment that caters to "geeks" in the same way marketing caters to "creative types,” adds Skinner. “They also need to realize the salary demands in this space are escalating.”

This story, "Why data scientist is the hottest tech job in retail" was originally published by CIO.

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