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Data Science Skill Gap


Inarguably, data scientists are the most in-demand professionals in the talent market.   However, the LinkedIn Workforce Report of 2018 indicates that there exist more than 150,000 unfilled data scientists’ jobs in various parts of the United States.  This indicates the acute shortage of professionals in the industry. Furthermore, the demand for data scientists is expected to grow exponentially at the rate of 15% between 2019 and 2029. As a result, the data science skill gap ought to grow if the required measures are not taken.

Why does the Data Science Skill Gap exist?

The Data Science skill gap is becoming a great concern for the industry and before the industry experts go on addressing the issue. There arises the need to understand why such a gap prevails in the industry.  So, let’s understand the reasons behind this Data Science Skill Gap which are as follows:

Sudden Rise in the Volume of Data across the globe  

Over the last few years, the creation of data has taken place at a faster pace. Almost 90% of the world’s data has been created in the past two years.  This indicates the rising demand for data scientists who can use scientific methods, disciplines, frameworks, and procedures to develop this data into useful insight and structure.

The increasing volume of unstructured data needs special attention which becomes possible with the combined use of Machine Learning, Artificial Intelligence, Statistics, Computer Science, and Information Science. The Data Scientists professionals are potent to convert this big data into usable information for the optimal operations of the company.

Lack of Education and Training for Data Scientists

Evidently, Data Scientist is the fastest growing profession across the globe and there exist professionals in smaller numbers to perform the role. Unfortunately, the industry has a scarcity of professionals with relevant skills such as a strong background in computer programming, data modeling, and statistics. These technical skills are mandatory to cultivate a pool of talented workers in the industry.

Thus, there arises the need for inclining more towards the education and training programs to incorporate disciplines and direct the skills towards the tight talent market. Alongside, the educational institutions still need to formalize data science into a degree and curriculum with a major in computer science and algorithmic construction. However, this isn’t the shortcoming on the end of educational institutions as the explosion of the data in the industry was unexpected and sudden.

Thus, the lack of training and education has impacted the ability of the industry to screen the right talent which has further resulted in a significant shortage of Data Scientists.

Underutilized Work Force

Besides, the shortage of Data Science Skill gaps in the industry there exists an additional issue that has given a boost to the issue. The dependency of the workforce on manual tasks instead of sought-after skills is the emerging problem. Hence, the core value of the Data Scientist gets hugely tied to expertise through which the generation of data models, algorithms, and insights get their value. The mastery over programming languages like R, Python, SQL, etc helps to provide uninterrupted services for the project.

Unfortunately, at present data scientists are bound to perform routine tasks which result in failure to put advanced skills to optimal use. The studies show that most of Data Scientists’ time gets spent gathering and cleaning the data which amounts to 41% of the time. Furthermore, only 31% of the work time gets is optimally used to build and run the data model which is the actual job of the Data Scientist.

Industry’s Response to Data Science Skill Gap

The study suggests that in the year 2018 Data Science job postings exceeded the number of job seekers indicating the clear scarcity of skilled Data Science professionals across the globe. Additionally, according to reports, the gender gap in the STEM field is quite prevalent too, where in every 3 men only 1 woman is employed or skilled to be employed in the sector.

On the other hand, the various universities across the globe are responding well to the demand for Data Scientists by ramping up the degree program which includes curriculum relating to Data Analytics and Machine Learning too. Since 2010 more than 830 Data Science programs have been designed by over 500 universities of which the Master’s program in Data Science is gaining immense popularity. 

Moreover, the pioneer companies like Cognizant, IBM, Amazon, etc have taken the steps ahead to reskill the existing employees with Artificial Intelligence (AI) and Analytical skills. Such an in-house education curriculum encourages the internal talent in the organization. A Shanghai-based Company, Transwrap has launched its own university to provide data literacy.

Final Words

Addressing the Data Science Skill Gap is certainly the emerging challenge that the industry and educational institutions are trying to tackle well. However, the growing demand for skilled Data Scientists is growing at a faster pace and these training and learning establishments are required to accelerate their pace too.  Thus, to structure more unstructured data, the Data Science skill development shall be duly structured.

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