Citizen data scientists are on the rise
Published May 19, 2020
Plus: tools for becoming one yourself.
You won’t see any job postings for this role. But that doesn’t mean it’s not one of the most valuable positions in any company right now, drawing on specialized skills and using a vast range of technological tools to provide organizations with insights.
This gem of a staffer would be the citizen data scientist — not quite a pedigreed data scientist, but still a data nerd by any other name — whose real title may be “analyst” or “strategist” or “engineer.” The phrase citizen data scientist, coined by Gartner, has connotations of advocacy. As in: “I’m making a citizen’s arrest!” In fact this isn’t too far fetched, since the citizen data scientist does take matters into their own hands.
Who needs a PhD when you can use Tableau?-citizen data scientists
What they grab instead of a person, though, is one of a growing number of analytical tools that can show growth, stalled progress or inefficiencies inside a company. Why is our revenue-to-cost ratio so high? Why has the win rate gone down? Far from a crusader, the citizen data scientist is often just a perpetually curious person, someone who wields technology to get answers and abides by the mantra: ‘Who needs a PhD when you can use Tableau?’
Born from necessity
The amount of new data in the world increases exponentially. The number of data scientists do not. In 2011, McKinsey noted in its comprehensive big data report, that the world was already running short on data scientists. By 2018, McKinsey calculated, America could be lacking between 140,000-190,000 people with “deep analytical skills.” That was on top of a deficit of more than 1 million manager types who would not have enough knowledge to look at data analysis and use it to make strategic decisions.
Flash forward to 2018’s LinkedIn Workforce Report, and the McKinsey prediction proved eerily accurate. LinkedIn noted that year that “demand for data scientists is off the charts.” In 2018, the country saw a shortfall of “151,717 people with data science skills, with particularly acute shortages in New York City (34,032 people), the San Francisco Bay Area (31,798 people), and Los Angeles (12,251 people)”.
New platforms for the win
So the citizen data scientist stepped in, filling all sorts of gaps inside companies. They may not have sat through academic lectures on linear regressions, but they did know enough math and science to help their companies maneuver. At the same time, a new crop of software companies sprouted up to assist and empower them.
Founders of companies like Qlik, Tableau, Alteryx, and Looker have made fortunes on the idea that complex data should be accessible and understandable to average people. And while you might argue that technology has created a problem — with internet-connected devices and analytics platforms generating more data every day — tech is also the ultimate leveler, giving people with basic skills the keys to the same insights as academically trained data scientists. In her TEDx Talk on the subject, speaker Allison Sagraves says most people can help cure diseases and tackle complex data problems using only the technology in their smartphones.
What’s next for citizen data science
To be sure, no one is implying that there’s no room left for highly trained data scientists. In fact, the need for them grows daily, as the amount of data in the world continues to explode. But for citizen data scientists, there’s always more learning to be done, and we’re thrilled to help.
Take a few minutes to complete the courses above. With just a bit of data science under your belt, the possibilities are endless inside a company, from figuring out how to streamline and automate, to hyperautomation and beyond. In fact, Gartner, who first spotted the citizen data scientist in the wild back in 2016, has a new prediction: by 2025, citizen data scientists will become so numerous that the lack of data scientists will no longer hinder the adoption of data science and machine learning inside organizations. To citizen data scientists, we say: more power — and powerful platforms — to you.