Career in Data Science post COVID

17Dec - by aiuniverse - 0 - In Data Science

Source: techstory.in

The coronavirus pandemic has transformed the lives of thousands of employed professionals all across the globe, including the ones in the data science industry. This crisis brought upon a new normal of working from home and pushed analytics to the forefront. Analytics professionals had to alter the way they work to keep up with the times. 

Data analytics and data science professionals who have been working in the industry for a while would understand how the COVID transformation will affect the field. However, a junior-level professional who is just starting out his/her career would experience a different scenario than what they expect. The pandemic might be tormenting for new graduates or amateur data scientists because more companies have no interest in recruiting fresh analytics professionals. That is why it is more important than ever to build your resume with a certification course. Here is how the career in data science will be different post COVID:

1. Increased competition

With virtual hiring and remote working in place, the norms of recruitment have changed. Companies are no longer required to hire talents from their area. This will create more competition, especially for amateur data scientists and freshers who have just begun their careers. Graduates will now be competing with not only the professionals from their own city or country, but also with those living thousands of miles away. However, there is an upside to this. This has also increased opportunities for data science professionals who can now apply for a job outside their country and gain a better salary. 

In order to stay relevant amidst this crisis, it is important for young data science professionals to gain appropriate skill sets and upskill themselves continuously. There are several online edtech companies that offer basic as well as advanced data science and AI courses. By enrolling yourself in one of these programs, you can help yourself sustain during these trying times. The landscape is evolving and businesses are relying heavily on advanced technologies. In order to stay ahead of the curve, it is important for data science professionals to continue learning.

2. Isolated learning process

Upskilling has always been an important aspect of the career of a data scientist. However, now that the pandemic has disrupted how businesses work, many want to hire professionals who have advanced skill sets. So, upskilling has become more important than ever to make advancements in the field. According to a LinkedIn report, 64% of professionals like data scientists have increased their focus on learning during the lockdown. 

However, since the companies have mandated working from homes for their employees, the learning and upskilling process has become isolated. Before COVID, companies offered training programs and in-person workshops for young data scientist professionals so that they could learn the skills needed for the business and get accustomed to the new workplace. The lockdown has omitted the process entirely and professionals have to rely on online programs to learn these skills. Moreover, these data scientists will be working from home for a long time that restricts their communication with their teammates, thus impeding their learning process.

On the other hand, online programs have become the only source for the new data scientists to enhance their skills and gain the knowledge they need to work in the field. It is important that you select the right online course that provides you with practical experience, interaction with the teacher, and other scientists. With the right program, you will be able to take on any challenges you might be facing in the workplace.

3. Increased efforts for collaboration

Data science is one of those fields that require immense collaboration between the team members to solve a problem. Through this effective collaboration, the data scientists are able to help the company enhance its business operations, create better products, and make informed decisions. A data scientist cannot work in isolation and collaboration is what will determine the success of the project.

This collaboration is especially important for new data scientists who have just joined the company. But, thanks to the pandemic, data scientists and analytics professionals are working by collaborating online. But these online collaborations are filled with challenges that require in-person training to understand the problems and business better. These challenges reduce the efficiency and productivity of the data scientists and create a large communication gap between the team members and the supervisors. 

In the field of data science, asking the right questions is important to solve business problems. With online collaboration, amateur professionals will face issues asking the right question at the same time leading to ineffective collaboration and hammering their work. That is why data scientists have to make a lot of effort to communicate in times of online collaboration.

4. Increased contract-based hiring

Another transformation occurring in the workplace post COVID will be contract-based hiring. This is applicable to almost every profession in the world including analytics professionals and data scientists. Once the pandemic cedes, companies will employ cost-cutting measures and hire freelancers, contract-based employees, and gig workers. This will allow them to keep the employer’s tenure for a limited time and avail data science capabilities for a specific project. 

Even though recruiting freelancers or contract-based hiring is beneficial for the businesses post COVID, it will bring added challenges of increased competition. Even when you want to be hired full-time, you might only be recruited as a contract-based worker because contract-based workers have cost edition benefits and flexibility in the organization. Companies realize that employees don’t have to be in-office or on the payroll for certain functions. 

Post-COVID, with the perspective of cost-cutting companies, will be looking for people who are generalists, instead of specialists. And that is why young data scientists need to have more than domain-specific knowledge. They have to resell themselves to have an understanding of the overall field of data science. And the best way to do that is through a data science course in Bangalore that you can take from the comfort and safety of your home. 

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