AI is taking over data science jobs by carrying out data processing and visualization works

From making drugs to delivering packages, artificial intelligence is disrupting many different sectors like never before. The possibilities of technology are leaving everyone in awe. Truly, the worldly applications of artificial intelligence are arming up to automate anything and everything. At a time when artificial intelligence is at its peak, we are bound to discuss its adverse side. Although technology is minimizing human workload, in some cases, it is stealing the job from humans. In the worst-case scenario, AI is taking over data science jobs from mankind in 2021.

While artificial intelligence is moving all the heavy rocks, it still induces an array of fear among people. One reason for this is because of the scary sci-fi movies we have come across. Many of them portray technology and automation as human enemies. Besides, people are also terrified of the fact that machines are replacing their stance in the workforce. Today, many of the heavy machinery works in manufacturing houses, factories, and the shipping industry is being carried out by machines. But originally, despite the hardship, human laborers did the work and were getting paid for it. What initially started as a wipeout move to replace time-consuming jobs, is now taking over intellectual works like data processing. Data science is a vast field that employs and sorts many big data-related issues. Technology has been spearheaded to be the core of many business decisions in the 21st century. Owing to its hype, the demand for data science jobs has also drastically surged. For over a decade now, being a data scientist is the hottest job in the tech sphere. Maybe, not anymore. AI is taking over data science jobs by carrying out whatever big data-related works they do. Without much effort, automation can process, sort, and analyze data, and make well-informed business decisions.

The Routine of Data Scientists

In order to learn how artificial intelligence is slowly replacing data scientists, we need to take a look at the routines of data scientists. Data scientists are professionals who take data from their repository in order to design, build, and test advanced models, based on machine learning algorithms. Their frequent tasks include preparing data, cleansing, checking for correctness, identifying outliers, and empty records. Besides, data scientists also detect prediction features and represent them, identify obsolescence of models, build basic models through intuitive interfaces, etc.

What are the Tasks that AI is Automating?

As the influence of artificial intelligence has spiraled in the digital world, it leads us to a debate on how automation will take over human jobs. Because of the recent advancements, we don't even have a choice to think of 'how,' but are moving towards 'what' jobs profiles will be filled by AI in 2021. One thing that stands first in the line is data science. Yes, to be precise, companies are paying a fortune for data scientists today. Although data scientists play a big role in business decision-making and problem shooting, organizations still prefer to look for an alternative that could cost them less.

Already, emerging AI algorithms are used to analyze data and provide solutions similar to those provided by data scientists. Automating the data processing tasks is more likely to surge in the coming years as it is easy for data professionals to get what they need without requiring human intervention. According to a Gartner report, around 40% of data science work was anticipated to be automated by 2020. As a result of this, the demand for data scientists has fallen flat. On a general scale, AI is taking over data science jobs without much hesitation. It can surely outperform data scientists in terms of speed and risk management. However, one thing that still keeps automation away from certain data science tasks is human intelligence. Although machines can take over the programmed routine tasks, troubleshooting and sorting a problem would be difficult for artificial intelligence.

While we talk about the critical points that keep the machine from becoming human competition, let's also look at some of the data science routines that AI can effortlessly take over. Artificial intelligence and data science work in accord to improve each other's efficiencies. A dynamic, multi-faceted decision process obtained through automation will outperform any single algorithm, no matter how advanced, by automatically testing, iterating, and monitoring data quality. In a nutshell, automation can genuinely take over lower-level tasks without any hesitation. Besides, if we move out of the job replacement bubble, artificial intelligence could even stand by data scientists' side in a supportive way. They can function as intelligent assistants to data scientists, allowing them to run more complex data simulations than ever before.

Machines are Pumping up the Skill Demand

The AI transformation is introducing a quest for special skills in the job market. Even in the data science field, the wave of automation has spiked the demand for specialized skills that data scientists need to possess in order to sustain this storm. They are openly keeping the bar of expectation high for many data science professionals with companies adding up more skill demands to their hiring process.