Data Science Jobs Will Completely Disappear in 2030! Is this a Crisis Time?

Is data science dying? Is data science job market oversaturated? Here we discuss this issue.

Data science job is the most promising and in-demand career option for a skilled professional. This article analyses data science as an oversaturated field. Data science will be around for quite some time.

Data has become an indispensable part of the 21st Century with our society witnessing rapid digitalization in the last couple of years. Most companies worked to solve very similar business problems with data science. Due to this, it wouldn't be necessary for data scientists to come up with novel methods of solving problems. The good news is that most data scientists are working on existing  Artificial intelligence projects. But, predictions say that ML engineers would replace data scientists in the coming years and this role could easily be replaced by a machine learning engineer.

Does a Data Scientist have a Foreseeable Future?

If technology has been disrupted, there has been technology to replace almost all of the work that is done in the data science field. According to studies, only 57% of enterprise organizations use data and analytics to drive strategy and change. And 95% of employers said that data science and analytics skills are hard to find. Many companies think that all data science jobs must be based on cutting-edge technologies, which would ultimately slow down hiring data scientists in the next few years.

Will automation kill data science jobs?

Automation will act as a supplementary tool that will boost data science tasks and make them more efficient. Bots can take care of lower-level tasks, whereas data scientists can take care of problem-solving tasks. This combination of human problem-solving and automation will, moreover empower data scientists, rather than threaten their jobs. There will be more technological advancements coming up in the future. However, it is important to understand that data scientists possess a very important skill. Which is very difficult for artificial intelligence to emulate.

Lack of data science guidance:

Another major cause of the industry's human resource deficit in the data science domain is a lack of proper awareness about job requirements among the aspirants. Data science is a big subject and students who try to learn everything ends up being a jack of all trades and master of none, which isn't what businesses are looking for right now. Many firms have a data-related requirement that needs candidates to have a thorough understanding of various parts of data science.

Is data science oversaturated, and will the field be replaced?

Many companies hire data scientists to solve data-driven problems at these organizations. The role of a data scientist is to add value to an organization with data. And in most companies, only a very small portion of this involves building ML algorithms. The use of automated tools like auto Machine learning and data robot was raised to solve business problems. But these tools have a fixed set of algorithms to find a problem and to solve it. And also data robots can't do data pre-processing or any of the heavy lifting that comes before model building. The values a data scientist provides to an organization lie in their ability to apply data to real-world use cases. As long as a data scientist is able to solve problems with the help of data and bridge the gap between technical and business skills, the role will continue to persist.