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Is data science still the future?

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Retail, Healthcare, e-commerce, IT, software- what ties all of them together? One technology: Data Science.

With the advent of new technologies and the growth in the industrial landscape, we need to see where the entire industry of Data Science is heading towards. Of course, it was one of the newest technologies in the past, and everyone wanted to be a data scientist, but is it the same today?

Data is the oil that runs every industry today, so occupations surrounding data will never be out of fashion. However, given the rapid growth of technology, one can question whether Data Science is still the future. Everyone has had multiple questions, especially from students who are going to start a new career or already working professionals who want to switch careers.

This article will discuss the demand for data science, its replacement, and alternative career options for data scientists. We’ll also try to ask the burning question of whether or not students and working professionals should pursue careers in this field. 

Is the demand for data science still high as before?

Data Science specialists have been in high demand in recent years as the amount of data generated has increased. 

All organizations want to make accurate and data-driven decisions for their organizations and consumers, which is why they require specialists who can extract relevant insights from data. According to recent studies, this need will not diminish as the amount of data generated every day increases.

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Many industries have seen a downturn due to the volatile nature of the market and businesses, and yet the demand for data science professionals has not changed. 

Remote work, Hybrid work, Work from Home are all things of reality now in major industries. 

Yes, the demand for Data Scientists is still high. 

According to recent statistical studies, job opportunities for computer and information research scientists, including Data Scientists, are projected to grow 15% from 2019 to 2029. This growth is faster as compared to the average growth for all other occupations. 

Data Scientists assist organizations in understanding data distribution and sharing relevant patterns and trends with decision-makers, allowing these organizations to make smarter decisions. They use powerful algorithms and machine learning approaches to detect patterns and trends in data that a human analyst might miss.

What is the replacement for data science?

Data Science is definitely here to stay. New technologies and practices are emerging every single day, similar to other industries that have the capacity to replace certain aspects of data science. For example, automated machine learning technologies are gaining popularity, and they may help businesses extract insights from data without the need for a data scientist.

Yes, automated technologies may accomplish specific tasks and potentially replace humans, but they cannot replace the knowledge and abilities of a professional data scientist who has spent years working in this environment.

Some aspects of data science, which are repetitive and cost time and money, will definitely be automated in the future, but the need for human insights and expertise will remain. 


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There have been more developments in other data-related industries as well in recent years. Due to these advancements, many critics believe that Data Science is not required anymore, but that is absolutely wrong because all these technologies are all branches of Data Analytics and help each other.

The foundation for AI and ML has been made by data science by providing the necessary data and algorithms for these technologies to work.

Artificial Intelligence and Machine Learning are methods employed to automate some of the processes performed by Data Scientists to save time and make them achieve more in less time. However, Data Scientists are still required to build, test, and enhance these models. 

They also provide a human touch by interpreting the findings of these models and providing insights to organizations.

What are the other career options for Data Scientists?

There are many other professions into which Data Scientists can seamlessly transition into Business Analysts, Data Analysts, Machine Learning Engineers, and Data Engineers. This is possible because all these professions are variations of Data Analysts.

All these positions require very similar skill sets, and all of them fulfill different roles for an organization that ultimately helps in business development.

  • Business Analyst: Business analysts detect business challenges and opportunities and deliver solutions to improve a company’s overall performance. They are mostly used to create company strategy.
  • Data Analyst: They also work with Data Scientists to find patterns in raw data and make an analysis of the received pattern so that it can be used to make informed business decisions. A Data Analyst is expected to obtain, process, and evaluate data using statistical methods. 
  • Data Engineer: They work a lot with Data Scientists and Data Analysts to make sure that data is accessible and available whenever it is required. Data engineers are expected to plan after research, construct from scratch, and maintain the networks needed for data processing and storage. 
  • Machine Learning Engineer: They work closely with Data Scientists and Engineers to make sure that the machine learning models they create are efficient and accurate. Machine Learning Engineers are expected to build, test, and implement machine learning models.
  • AI Researchers: They are in charge of researching and upgrading AI technologies such as natural language processing and computer vision.


Many sectors still see data science as the way forward. The demand for data science specialists remains high. As new technologies and practices emerge, that may replace specific aspects of data science, some portions of the field may be eliminated, but not the entire profession. Some portions of data science will be automated in the future, but human insights and expertise will still be required.

Data Scientists have numerous different career options in the tech industry, making this field even more appealing: whether you are interested in Data Analysis, Business Analysis, Data Engineering, or Machine Learning Engineering, there is a career route for you in Data Science. While AI and machine learning are developing technologies that will augment Data Science, they are not alternatives. 

If you appreciate working with data and want to make a difference, a career in data science will be rewarding and profitable. 


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