Data scientists

Since the beginning of 2020, the world has been undergoing rough times. Despite the numerous hurdles people stumped on, one thing that climbed up the ladder is technology and the changes it introduced. Following the surge in digitization, data science continued to evolve and companies across various sectors also opened their doors to recruit more data scientists. But looking beyond the pandemic hit years, data scientists need to upgrade their skills to survive the upcoming times.

Starting from healthcare and education to transport and entertainment, the dominance of data science is far fledged than anybody’s thoughts. Data science is spread across various domains, going beyond the tech and software sectors. Data scientists are one of the most sought-after roles in the corporate sphere with organizations welcoming more professionals into their office space every day. But things changed when people were pushed to work on remote modes. The lockdown has reinforced the notion to ‘work smart’ in terms of advancing data science skills for maximizing professional prospects. Many companies found themselves in the middle of reinventing their technological aspect to strengthen the falling economy. There has always been a technology gap between what the companies expect and what data scientists could offer. The thirst for more data science skills has further created a void during the pandemic. Engaging with data and carrying out data analytic processes to gain insights are the basic tasks of a data scientist. But as the tech sphere has evolved and companies ask for more from them, data scientists need to upgrade their skills to survive 2022 and beyond. IndustryWired has listed a few data science skills that could help professions perform well in the upcoming years.

The Emergence of Quantum Data Scientists

Quantum computing and quantum information are still in the first phase of development. But once they start flourishing into the commercial market, data scientists will be threatened to learn more about quantum and how to employ them along with data science. Besides, when data science and quantum computing starts working together, it will represent new opportunities in every sector. For example, if you are calculating a bunch of initial inputs on a classical computer, you have to run them one at a time. But with the help of quantum computers, things will get easy as they can perform multiple calculations at the same time. 

As quantum computing holds the speed and sophistication to streamline calculation, data scientists will be put in a tough spot to adopt them. A new frontier called ‘Quantum Data Scientist’ will likely emerge in the upcoming years. Quantum data scientists must understand quantum mechanics and how to use a quantum algorithm to solve a particular problem.

Machine Learning as the Catalyst of Skill Development

Machine learning has always been at the heart of data science operations. But its functionalities are often underestimated in the data science circle. Fortunately, the future will open new doors where machine learning stands at the forefront of data science. Machine learning’s ability to generalize knowledge from data will turn out to be an important factor for data science’s development. The disruptive technology will act as a catalyst to increase relevance. 

Statistics is a common technique used in machine learning and data science. Therefore, in the future, with the help of statistics, machine learning will help data scientists to train datasets and fine-tune some models or algorithm parameters. It will also extend its limits in data integration, distributed architecture, data engineering, data visualization, and data-driven decisions.

Coordinating Data Science with Cloud Computing 

Many organizations from across the globe are moving to work in the cloud. Although some companies started the terrific mission during the lockdown, they realized that cloud computing could actually fast-track routine processes and cut down costs spent on the physical environment. Besides, cloud computing also helps companies scale up their IT framework according to the demands. Therefore, data scientists should also try to find ways to correlate their data science skills with cloud computing.