Mariah Walton leans forward and daubs a canvas with paint. At home, she works in oils, slowly building the paintings she has been doing since childhood. At work, she believes the skills that make her an artist, make her a better data scientist at LinkedIn.
"I'm a visual learner. I actually see things in my head when I look at problems. That translates really obviously into art," said the 29-year-old. "But it's also how I do my data analysis."
People like Walton are in demand these days. A 2015 survey by global recruiting consultant Harvey Nash found that topping the wish list for chief information officers were employees with the skills to mine all the big data the digital revolution has created, and to unearth the trends and solutions these billions of text files may contain.
"Big data is becoming an effective basis of competition in pretty much every industry," said Michael Chui, a partner at the McKinsey Global Institute. "Whether you are looking at health care and the ability to provide personalized medicine, or you look at logistics or operations that are trying to improve the efficiency of the supply chain."
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Still, with the exception of a few notable firms like Amazon and Google, Chui said many companies have not benefited as much as expected from big data's insights, in large part because there are not enough people with the deep analytical skills needed to mine the data.
Because of this, Chui stands by a 2011 report from McKinsey predicting there could be a shortage of between 140,000 and 190,000 of these workers by 2018, as industries well beyond tech look for workers who can help them improve their companies by utilizing information gleaned from big data.
LinkedIn's head of data recruiting, Sherry Shah, describes the job market for these candidates as being "very hot right now" as the data field is "very sexy."
"So its superhard to find the right talent," she said.
Shah said the online networking site is looking to hire more than 100 data scientists this year, a 50 percent increase from 2014. And because Mountain View, California-based LinkedIn is not the only Silicon Valley company vying for these potential employees' talents, she said, "there is always a bidding war."
Shah would not say what these data scientists are paid, but noted that a person with a Ph.D. will command a six-figure salary, while the others are paid "competitively."
To find the right candidates in this competitive market, Shah said LinkedIn searches its own website, recruits at tech talks and conferences, and looks beyond the traditional pool of applicants for these jobs.
Shah said while 80 to 90 percent have a computer science background, the company also looks for employees in industries like biomedical or political science. Both industries, she noted, use a lot of data so the workers would replicate some of the work they did in their prior jobs in the tasks they do at LinkedIn, using different data.
Thirty-one-year-old Jerrod Lowmaster is one of those recruits. He received his undergraduate degree in Near Eastern languages and civilization from the University of Chicago and a master's in international economics from Johns Hopkins.
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"This is kind of my third career," said Lowmaster of his role as a data scientist for LinkedIn's growth group, which is focused on expanding the company's user base.
Now settled in San Francisco with his girlfriend and his dog, Lowmaster worked in intelligence for the NSA and then on a renewable energy project before joining LinkedIn.
"The one common thread I think that really unifies those jobs is I was in a place that had a great deal of data, and it really wasn't structured and there were interesting and critically important business questions we wanted to ask the data," he said.
Lowmaster added all the jobs require finding the right techniques and ways to look at the data, to give executives or decision-makers the information they need to decide what to do.
Self-taught in computer languages commonly used in data analysis, Python and SQL, Lowmaster believes the most important skills a future data scientist can bring to the table, beyond the requisite technical chops, are an inquisitive mind and to be customer oriented.
McKinsey's Chui said future data scientists also need to be skilled in statistics, and to be able to tell stories with data, to make it understandable to a variety of people.
That is what Walton does in her role on the business analytics team. She works with LinkedIn's sales force, looking at why certain members click on certain ads. The sales team can then bring this information to the company's advertisers so they can be more effective in targeting the right audience on LinkedIn's site.
"We have millions of visitors to the site each day, and we are logging every page view and click," said said. "I am trying to understand in aggregate what these different people are doing."
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She also looks at the data in smaller slices, segregating it by a member's job title or location, all in an effort to try to figure out why unconventional audiences are interested in certain ads and why.
A chemical engineer by training, like Lowmaster, Walton's path to LinkedIn was a circuitous one. After earning her undergraduate degree at the Rose-Hulman Institute of Technology, she moved to Colorado where received her master's in climate science from the University of Colorado at Boulder. Deciding she did not want to teach, she joined the solar industry, helping a California-based company maintain its meteorology stations. The firm went bankrupt, so she moved back to Colorado before returning to California about a year later.
As for her job at LinkedIn, where she has been since April of last year, Walton said she loves it. Animated and enthusiastic, she said while coding is a large component of her job, her favorite part is seeing a project through from beginning to end.
"A large part of my job is managing a project, which means I get to talk to a lot of different teams," said Walton. "I get to see a lot of different people come together and I get to see a final product."
A fitting observation, and job, for someone who has been recording what she sees since she was a child.
