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Citizen Data Scientists vs Expert Data Scientists

Citizen data scientist vs Traditional data scientist

In recent times,  there is widespread availability of steady data stream and efficient BI (business intelligence) tools to extract knowledge from raw unprocessed data. Businesses are slowly realizing that they don’t need highly specialized data scientists for tackling every single task. Companies believe that professionals with the right skill set can handle different data-related assignments. Hence a new job function called ‘citizen data scientist’ has come into the foray. The role of a citizen data scientist is expected to grow by 5 times compared to that of a traditional data scientist within the next 2 years.

In this blog, we make a comparative analysis of the roles of citizen data scientists and traditional data scientists.

Table of Contents

Who is a citizen data scientist?

A citizen data scientist is someone who creates data models using innovative tools to provide valuable insights for the business. This role was basically created to address the scarcity of talented data scientists.  Though this job role is not defined clearly, it complements the technical acumen of traditional data scientists.

A citizen data scientist uses software features such as data pipelines, pre-built models, etc to built no code models. As they are an integral part of your organization so they are familiar with the business’s pain points, strategies, clients, etc. Below is an info-graphic talking about the characteristics of a citizen data scientist.

Citizen Data Scientists vs Expert Data-1

Who is an Expert data scientist?

Traditional data scientists collect, clean, and analyze large sets of data to solve business problems. They have significant experience in statistical programming languages, such as Python and R programming. Most data scientists use R programming to solve any statistical problems.

Traditional data scientists should also have experience in using Hadoop platform. Hadoop can be used for data exploration, data filtration, data sampling, and summarization. They are also familiar with data analytics tools, including Google Analytics. Besides they have a Master’s degree or a PhD in the field of Computer Science or mathematics. So usually, companies face a dearth of experienced and qualified talent for the role of data scientists.

Till now we got a fair idea about who are citizen data scientists and who are traditional data scientists. Next, we will compare the traits of both so that you are able to decide who is the best fit for your organization.

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Citizen Vs Expert data scientist: Which role is perfect for your organization?

If you are not completely sure what type of data scientist do you require for your business, a comparison might prove useful. The following differences illustrated in the tabular form may help you decide who will be perfectly suitable for your organization.

Citizen Data Scientists vs Expert Data Scientists-2

Why businesses are turning to citizen data scientists?

So now when we know the difference between the two types of data scientists, it’s quite clear why businesses are opting for citizen data scientists. This new genre of data scientists brings their own unique skill sets in closing the gap in business process understanding.

Taking the example of Sears, a famous integrated retailer, which introduced citizen data scientists to enhance their customer segmentation. This helped the retailer in drastically reducing data preparation costs as citizen data scientists took care of data exploration, visualization, and insightful decision making.

Up-skilling or re-skilling employees to pursue advanced data roles can help organizations to use data in a better way. This ultimately leads to greater cost savings, higher efficiency, and increased competitiveness. The next pertinent question is “ Do we no longer need traditional data scientists?” Nothing like that. The attempt is to strike a balance between the traditional and contemporary work approach. It lets small budget companies fulfill their analytics needs through existing employees who can handle BI tools. Also, it enables expert data scientists to focus on the organization’s complex data requirements.

As data keeps growing in volume, it is recommended that top companies explore the role of citizen data scientists. Skyl.ai is one such SaaS platform that offers a guided ML workflow for citizen data scientists to work faster on unstructured data. Start your AI/ML journey today!

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