Data science is the process of preparing data for analysis, which includes cleansing, aggregating, and manipulating data for performing advanced data analysis. Mathematicians, trend-spotters, and computer scientists are all needed for data science jobs. Data scientists are in charge of collecting, analyzing, and interpreting massive amounts of data.
Data scientists can provide invaluable insights that transform the way we do business, resulting in more solutions and cost-cutting opportunities. However, most data science enthusiasts were unaware of how neural networks worked. Most businesses are implementing a data science strategy to increase revenue by automating various scenarios and replacing dozens of IT employees. As a result, the number of data science jobs is decreasing. Let’s take a look at why data science is a growing field with fewer jobs.
Why data science is a growing field?
Businesses across industries have recognized the value of data, which has increased the demand for a data science career. Data assist businesses in assessing the market and consumer base, which is quickly becoming an indispensable asset today. Data scientists must assist businesses in navigating the world of global data collection and application.
Since tools such as artificial intelligence became more accessible to businesses, data science has been on a roll. Experts predict that by 2025, 163 zettabytes of data will be generated, an incredible figure driven by the explosive growth of connected devices and enhanced networks.
Because data science is critical to so many industries, there is no reason to believe it will be anything other than a growing profession for many years to come. Data scientists are critical to the success of numerous businesses across industries, from securing business processes to meeting international data security standards to connecting new and vital patterns in business trends.
Why is there a data science job shortage?
The main reason for the industry’s shortage of data scientists is the lack of skills. Data scientists are highly skilled individuals who are expected to have both technical and non-technical skills.
Another reason is that data scientists used to spend days gathering data, cleaning data, and selecting features, but now many tools on the market can do these tasks in a matter of minutes, such as H2O and PyCaret.
Another major issue is that companies are looking for data scientists with several years of experience. As a beginner, they have no experience in the field of data science, and companies require experience, creating a stalemate for aspirants.
Conclusion
Data scientists can help your business ventures and make a significant impact on the global economy. In reality, however, things are changing at a rapid pace. Furthermore, we are losing data value because everyone will trust the tool that tries more than twenty machine learning algorithms with higher accuracy than data scientists who try only a couple of machine learning libraries with lower accuracy.
