The Rise of Data Scientists

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Data science has been used in physics and astronomy, but it is being applied to businesses and finance, manufacturing, and other fields. The demand for data science professionals exploded about two decades ago when businesses began collecting massive amounts of data, and a shortage of talented individuals, or data scientists, with a specific set of skill sets able to extract the most benefit from the available data (World Data Science, 2022). Data science is a multi-disciplinary field that converges programming, mathematics, statistics, computer science domain expertise, and communication skills, yet seldom organizations are able to find a data scientist that excels at all of them (Bansal, 2021; World Data Science, 2022). 

The World Data Science Initiative (2022) reports data science jobs were expected to grow by 364,000 in 2020, but the real number came in at 2,720,000. Data scientists became part of the solution to address the challenges of growing organizational data sets, and with a certain future that those data sets will become even larger (World Data Science, 2022) with support from rapid technology advancements. Data science professionals extract insights from data and discover trends using data-driven methodologies to support data-driven decision-making and to reduce the potential negative impacts of uncertainty, including building future roadmaps (Bansal, 2021) or predictions. 

Bansal (2021) states data has no value without the science, that it needs to be properly read and analyzed by talented, multi-disciplinary data scientists for businesses to leverage off of all its benefits. Deloitte Access Economics as cited by Bansal (2021), state 76% of organizations will increase spending in the area of data analytics, and the U.S. Bureau of Labor Statistics reports data scientists will grow to about 11.5 million by the year 2026.

The road data scientists travel to provide organizations with valuable insights, not only supports data-driven decision-making, but it leads to innovation (Bansal, 2021). These capabilities were not available 20 years ago at the level they are today, but technological innovation was one of the forces that uncovered the critical need for data science professionals. Another is the improvement of education as academia and industry join forces to develop information systems (IS) curricula that incorporates big data analytics (Mills et al., 2016) to better prepare graduates as they step into the data science field.


   

References 
Bansal, S. (2021, January 6). Why is data science important for you and businesses? Analitix Labs. https://www.analytixlabs.co.in/blog/why-do-we-need-data-science/ 

Mills, R. J., Chudoba, K. M., & Olsen, D. H. (2016). IS programs responding to industry demands for data scientists: A comparison between 2011 – 2016. Journal of Information Systems Education, 27(2), 131-140. ProQuest Central. 

World Data Science Initiative. (2022). Why data science is the most in-demand skill now and how can you prepare for it? https://www.worlddatascience.org/blogs/why-data-science-is-the-most-indemand-skill-now-and-how-can-you-prepare-for-it

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