Shortage of data scientists: can your company call on citizen data scientists?

Teaching data science to the people you already have on your staff can help alleviate the massive shortage of data scientists. Here’s where to find them.

Image: iStockphoto / fizkes

Gartner defines a citizen data scientist as “a person who creates or generates models that exploit predictive or prescriptive analytics, but whose primary function is outside the realm of statistics and analysis.”

Does this mean that people without formal training in data science can undertake data science work? This is an open question for organizations looking to develop their expertise in data science in the face of dire shortages of data scientists and the prohibitive salaries that these highly sought-after professionals can charge.

SEE: Hiring Kit: Database Engineer (TechRepublic Premium)

Where does citizen analysis work

To examine the issue of the citizen data scientist, it is helpful to start by examining where citizen analytics development works in organizations today.

The current sweet spot for citizen development and analysis is the development of Microsoft Excel spreadsheet reports and the use of no-code or low-code report generators that do not require much IT involvement. With these tools, citizen end-user developers can develop their own analysis reports and what-if analyzes. It’s also important to note that the majority of these analytics reports use structured data and not the unstructured big data that so much data science work depends on.

Enabling citizen data scientists

To move from simple analytics reporting to more complex data science work that involves structured and unstructured data and the generation of data models, there is a need to hone the data non-scientists so that they can acquire a working knowledge of data science skills.

Stephen Watts, writing for BMC, a software company, explains the skill set: “The right person is someone who understands the vision, mission and needs of the business, and how data helps propel their needs… . [He or she] can think outside the box, come up with data models and connections that go beyond what the average layman would conceptualize [and he or she] must be analytical. ”

SEE: The situation of data scientists: overwhelmed and underfunded (TechRepublic)

Watts goes on to say that “Being able to perform fairly complex data analysis is part of the job. It is important for a citizen data scientist not only to logically assess the data in front of him, but also to draw meaningful conclusions from it. that the person might not see.

Due to the emphasis on data know-how, when companies seek candidates in citizen data science, it makes sense to revisit the ranks of disciplines within the company (for example, the engineering, software development, data analysis) where some of these skills may already be residing. For example, an IT data analyst or software developer is likely to grasp the idea of ​​modeling data for analysis more easily than an individual in purchasing, marketing, or accounting.

There is also an added benefit if companies can develop employees who have business acumen and strong end-user relationships across the enterprise. These people might have more ability to understand and analyze the information needs of the business than a data scientist who knows math, statistics, and analysis, but has no working knowledge of the business.

Can citizen data scientists completely supplant data scientists? No. But they can lighten the burden on data science personnel.

Tech leaders, if your business wants to develop citizen data scientists, the most logical place to look for them is IT. Data analysts and software developers already know the data and know how to model it. They have worked with end users and can extract the critical business questions that data science needs to answer, and they also understand the need for quality data that has been properly cleaned and prepared before being questioned.

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Sean N. Ayres