Analytical sales and non-technical employees are democratizing the data science field. Gartner forecasts that over 40% of data science tasks will be automated by 2020. Organizations seek to turn non-technical employees into data scientists to combine their domain skills and data science techniques to solve business problems.
What does Citizen Data Scientist mean?
Citizen Data Science is a term coined by Gartner. They define it as a person “whose principal function lies outside the field of statistics and analytical systems, which develops and generates models using advanced diagnostic analytics or predictive and prescriptive abilities.”
They are non-technical employees who can use tools for data science to solve business problems. Citizen data scientists can provide the expertise that many data scientists lack in business and industry. Their business experience and awareness of business priorities enable them to effectively integrate data science and machine learning output into business processes.
How to Become a Citizen Data Scientist?
The quickest way to become a citizen data scientist is to upskill with your employer or become better skilled. Anyone who wants a career in data sciences but cannot go back to high school, a job in the role of a citizen data scientist can fit perfectly well. A Data Science certification may be an ideal training course. However, you can follow several different paths and depend on whether you work with an employer who wants you to retrain or position yourself for a new job.
For the sake of efficiency, working in a neighboring field is a good practice. A career such as backend software development or engineering can be a good fit because roles need an overview of mathematics, coding, computer science, and relationships. Moving from one of those mentioned above to a citizen data scientist role requires you to become competent rather than acquire a whole new level of skill set. Some people working in this field are already para-professional modelers and only have to demonstrate and prove their existing skills to play a role.
Each path requires extensive knowledge and the ability to use data software efficiently. More professionals are aware of the need to diversify their software competencies in a digital business economy, creating new, exciting roles that benefit them and their businesses.
Citizen Data Scientist’s role in an organization
A citizen data scientist is responsible for handling new data, using automated tools for processing big data and developing additional models to gain more insight. Its primary task is not to produce direct predictions on big data or develop prescriptive analytics but rather to build models and tools to achieve these objectives.
Citizen data scientists bridge the gap between actual (trained and graduated) data scientists and business owners who perform their self-service analytics. This analogy could offer a glimpse: a data scientist could ride 10 miles per hour. But a citizen data scientist may stick, warm up the car and drive ten miles for less money within less than an hour. The citizen data scientist will certainly not see the scenario as much as possible, but they will still do the job.
The citizen data scientist position is particularly unusual. Although the title exists for a couple of years, employers looking for a “citizen data scientist” have no job listings. In general, the position adds to someone’s current job description responsibilities. The promotion usually includes taking and passing certain data science classes relevant to the organization’s needs and can consist of certification.
Creating a position of “citizen data scientist” is a solution to the unavailability of data scientists. Most of the work generally that data scientists do typically addresses worldly operational tasks such as data quality validation, data sets fusion, and data source identification. These tasks take more time and are tedious. An “expensive” data scientist carrying it out is not very cost-effective. It is better to use someone far lower priced to carry out these tasks using automation.
Importance of Citizen Data Scientists in an organization
Data analytics experts typically concentrate on finding trends in data from past events (descriptive analysis) and expressing their results through dashboards, static reports, and graphs. Citizen data scientists, software technologists, data engineers, and IT engineers now have robust tools to solve business problems using more extensive data than their professional data analytics peers. They can create models that recommend the following best approach, identify the most likely prospects of purchasing a product, identify the loans that would most probably affect, and more.
Future outlook of a Citizen Data Scientist
Organizations are becoming more and more concerned with shifting to advanced predictive analytics. Traditional data scientists are often costly and challenging to come through at present. Citizen data scientists can handle this shortage effectively. The main reason for the growth of citizens’ data scientists is technology. For non-specialists, technology made it easier to fulfill the same objectives. Analytics and BI tools have been much more straightforward and include enhanced analytics in the last few years.
Most companies lack sufficient data scientists throughout the company. Still, they do have many qualified information analysts who can be citizen data scientists. They can perform complicated diagnostic analyses and build models that leverage predictive or prescriptive analytics, provided with suitable tools. This makes it possible for them to move more thoroughly and widely beyond the analytical reach of regular users.
Final career thoughts
Take certification classes, which provide you with the skills to be an efficient citizen data scientist. It could include certification in Tableau or Python or training in data science for an essential basis. You can work together with your company to reskill and get the proper accreditation if you have a strong knowledge of the business vision and need data.
Still, it is increasingly popular to become a citizen data scientist for people who are not prepared to enter a Ph.D. but qualified with data since there is a greater need for talented data professionals than data scientists to play the role. It makes a particularly lucrative profession for the right person ready to take his mid-level analysis and data modeling skills to the next level of work.