On March 11, 2020, the World Health Organization declared Covid-19 a pandemic. After a few weeks, around 16 million workers in the United States switched to remote work to help flatten the curve. This means approximately one-quarter of US knowledge workers had to work from home, and the number is still on the increase due to the restrictions imposed by states.
Workers who were able to transition to remote work were part of the lucky ones. During the peak of the pandemic, millions of Americans lost their jobs, while others worked high-risk jobs to make ends meet. The tech industry was the first to consider remote work as a permanent solution post-Covid. This article will highlight new data on remote work during the pandemic and its effects on some tech job salaries.
What we know About Remote Work During the Pandemic
- Experience matters when it comes to remote work: communication and productivity were difficult when remote work was new to workers. However, the months of experience has helped, and many workers have found strategies and tools to boost work satisfaction and collaboration.
- Professional connections were strained: remote workers experienced a strain in their professional connections at first. However, this improves over time.
- Collaboration tools are essential: these tools not only help workers with productivity, but they also improve communication. The result is a greater sense of belonging in remote work.
How Did Tech Salaries Fare During this Period?
Web development and data science are the focus of the article. Both jobs did well during the pandemic, and the demand for employees skyrocketed. More non-tech businesses needed help with data and the development of web services to cater to their now-remote business. This singular factor makes both jobs attractive for the future.
Web developers are software engineers that focus on creating websites through coding. These engineers need to know programming languages to be able to build a functioning website. Some of their other roles include maintaining coding or fixing bugs after an update.
There are three types of web developers, namely back end, front end, and full stack developers. As the name implies, a back end developer works on the company’s servers while a front end developer handles the customer-facing part of the app. This distinction of duties is essential to make sites run faster. When the responsibilities are split, data can be processed faster.
Full stack developers are engineers who are skilled in both back end and front end development. Web developers make an average of $107,161 per year in the United States, according to Indeed. The demand for web developers rose during the pandemic, and it is expected to continue with a salary raise.
The Covid-19 pandemic changed a lot of things including consumer behavior. Therefore, organizations rely more on data insights to help them enhance cybersecurity, productivity, employee retention, recruitment, customer service, and more. Data scientists need to explain risks, opportunities, and trends to nontechnical people so they can make better business decisions. Data scientists also help software programs learn in a process known as machine learning. When computers learn about the data, it increases the speed of development of other new processes. Many non-tech businesses sought out data scientists to help them with such tasks and this is why the demand for them increased significantly.
Data scientists earn around $100,000 per annum and this rate is expected to increase with the rise in demand for their services. Python is the most common coding language data scientists use. If you desire a career as a data scientist, you must learn Python. Luckily, you can use web resources like Bootcamprankings.com. With a consistent study routine for a few hours a day, you could learn a new skill that positions you in the forefront for jobs of the future.
It is not clear whether remote work will continue after the pandemic, but companies may decide to keep some part of their workforce remote. The remote working policy was adopted within a short time, and its result was positive. There is still a lot of work to be done before the policy can stand. One consideration is the salary. Should salaries be slashed or increased since some determinants of salary rates are no longer in play? Some argue that the main determinant of salary should be experience and value rather than location.