The world is in the midst of its worst health crisis since the Spanish influenza pandemic over a century ago. The implications of the Covid-19 epidemic to the global economy and the job market are simply staggering. In the US, a record number of people have filed for unemployment, and over 57 percent of people are worried about losing their jobs.
With millions of companies worldwide going under as the pandemic destroys local economies, people are researching ways of boosting their employability and protect their financial future. For those that find themselves in this situation, we have put together a list of the jobs and career tracks in the tech sector with the best prospects now and after the pandemic.
Artificial intelligence/machine learning engineer
Artificial Intelligence (AI) is a technology that seeks to teach machines to think like humans. Part of AI, machine learning is a technique used to create complex algorithms that learn based on experience and make accurate predictions.
AI and machine learning are becoming more and more pervasive in today’s world, with applications across every industry and area of human endeavor. In e-commerce, marketers use machine learning to collect and parse vast amounts of data to provide online customers an experience similar to what they would have in-store. Machine learning is also used to create targeted campaigns that increase sales.
Another important application of AI in the business world are chatbots, also known as conversational AI. Chatbots make it possible to quickly and efficiently answer customers’ main queries and problems.
H&M, the Swedish clothing giant, for example, uses these bots to help visitors to their website find exactly what they’re looking for. The company’s chatbots make suggestions to the customer on what they might want to try on based on their preferences.
French cosmetics manufacturer Sephora lets its users try their lipstick and eyeshadows on a photo of themselves that they share with the bot. The bot’s AI technology identifies the user’s facial features and uses augmented reality to apply these makeup tests.
As they replace humans, these chatbots have saved companies millions of dollars in salaries and immensely improved the customer experience. The most advanced of them can already answer open-ended questions in a human-like way.
To make this possible, engineers deploy Natural Language Processing (NLP), an AI technique that helps chatbots analyze and understand the language used by customers. Through NLP, chatbots have become so sophisticated that, in many cases, users cannot tell them apart from their human counterparts.
Personalization is now the focus, with engineers training chatbots on the different default responses and how they can make customers’ lives easier. NLP allows chatbots to tailor their responses, interpret and answer new questions and commands, and improve the user experience.
As the tech industry shifts its focus toward the emerging field of automation, demand for AI/Machine Learning Engineers is exploding. Engineers that can deploy NLP and other AI and machine learning techniques have a bright and financially secure future ahead of them.
These are among the best tech jobs for the future by most measures. From 2015 to 2018, the number of job openings for Artificial Intelligence/Machine Learning Engineer grew by an astounding 344 percent. The average base salary for an AI/Machine Learning Engineer is $146,085.
The data industry
From customer preferences to the price of a competitor’s products, companies collect and seek to use ever-growing amounts of data. This data can be extremely beneficial to a company’s bottom line, but first, you need to know how to use it.
There is a whole industry centered around the science (and art) of collecting, interpreting and drawing conclusions from data. Some of the professionals that populate this industry include data scientists, data analysts, data architects and data engineers. In this article, we look at two of the most popular, and lucrative, jobs in this nascent but booming sector: Data Scientists and Data Analysts.
A Data Analyst translates data into plain English, whether sales figures, market research, logistics or transportation costs. Their ultimate goal is to help companies make better business decisions. Their job may also involve creating visual representations to help executives get a better handle of the numbers.
Experts expect the number of job openings for Data Analyst to grow by 16 percent from 2018 to 2028. In 2019, Data Analysts were earning, on average, $118,370 a year.
On the other hand, Data Scientists collect and analyze vast amounts of data, and companies used their findings to make decisions critical to their economic performance. The Data Scientist turns massive lists of data into actionable recommendations that help a business achieve its goals. The big difference is that a Data Scientist also has coding and mathematical modeling expertise. Many hold an advanced degree and may have started their careers as Data Analysts.
The average salary for a Data Scientist last year was $120,495.
Software Developers build the programs and applications you use every day, from the app you use to listen to music to your Internet browser. But they don’t work in a vacuum—someone has to design all of those web pages and applications. These professionals—known as User Experience (UX) and User Interface (UI) Designers—are in high demand and command enviable salaries.
The jobs of UX and UI Designers are intertwined. These designers work together to create a final product that is intuitive to use and pleasant to look at. To put in a few words, the UX Designer conducts research and identifies problems customers face with a product. They then pass that information to the UI Designer, who uses it to create an attractive and functional design for the product. But let’s look at each role separately.
As the name suggests, a UX Designer job is all about the user experience. The goal of these professionals is to create a product that is as easy to use and as intuitive as possible. They conduct research that exposes the potential problems customers may face with a given product. Based on their findings, UX Designers make changes to a design or feature to optimize the user experience.
A UI Designer, on the other hand, is responsible for the overall design and look of a product. They choose the colors and font of a website as well as the style of each element of an application. They also assess the accessibility of a particular design. UI Designers use the information gathered by UX Designers to create aesthetically pleasing and functional designs.
These are just a few of the tech sectors and jobs that are “Covid-19 resilient.” As the drive for automation continues and companies’ reliance on technology grows, Artificial Intelligence and Machine Learning Engineers, Data Scientists, Data Analysts, and UX/UI Designers have a secure financial future ahead of them. Demand for the services of these professionals is booming and will continue to grow in the foreseeable future.