Data scientists are one of the fastest growing occupations worldwide. The term was coined by tech executives over a decade and a half ago, but it has morphed to a job position that is so prevalent that it is hard to find a company that doesn’t employ at least a few data scientists.
For the past two years in a row, data scientists have topped CompTIA’s State of the Tech Workforce report as the fastest growing tech occupation. Over the next decade, employment of data scientists and data analysts is expected to grow at a rate of 266%.
Data scientists have even been described by the Harvard Business Journal as the “sexist job of the 21st century.” So, with this description paired with rapid growth and six-figure salaries, what isn’t there to love? Fortune dives into what truly are data scientists, where they work, and how you can become one.
Depending on the company, industry, or career level, the day-to-day tasks of a data scientist may differ. But broadly speaking, data scientists use models and algorithms to explore, analyze, and optimize data—then use their conclusions to solve problems and communicate results and solutions through visualizations.
Data scientists can work in practically every industry, the likes of healthcare, sports marketing, and urban planning. And data can be used for example to predict weather patterns, analyze social media traffic, or evaluate clinic trails.
Data scientists are familiar with programming languages like Python, R, and SQL as well as machine learning, data visualization, and data mining tools.
Having soft skills are also important to a data scientist’s job—like problem solving, critical thinking, and project management. Since you will likely not be the only data scientist in a team, knowing how to effectively communicate and work collaboratively is also key.
It is somewhat difficult to find a tech company without open jobs in the field of data science. But data scientists are also not just being hired at Big Tech companies. They are in demand across industries at places you wouldn’t first associate with data science.
Walmart, for example, currently has dozens of open positions in data science and analytics. A quick search on LinkedIn will populate thousands of data scientist positions at Fortune 500 companies like CVS and Starbucks as well as even government entities like the FBI.
Wade Fagen-Ulmschneider, a teaching associate professor of computer science at the University of Illinois, says every one of his top students have been able to secure multiple job offers in data science—with some going on to work at companies like Google, Microsoft, and Deloitte.
He adds that outside of tech corporations, data scientists are also in high demand. Students have gone on to successful careers at places like Caterpillar as well as top consulting and accounting firms.
Similar roles to a data scientist include data analyst and big data engineer.
While salary will vary based on educational background and years of experience, data scientists largely make six-figure salaries—especially those with a master’s degree.
The U.S. Bureau of Labor Statistics reports that data scientists earn $103,500 on average—with those working in the scientific research and development services industries making closer to over $118,000 on average.
According to research from Dice, a tech job website, the average salary of a data scientist is $117,241.
“There’s no downside for people learning data science, or any of the kind of underlying skills that are required for AI,” says Art Zeile, Dice’s CEO—adding that despite layoffs over the past two years, the tech unemployment rate remains low, at 2.1%.
Whether you’re just starting out in your career or already mid-journey, learning about data science can be the secret to a secure future due to substantial growth in positions and salaries. Luckily, there are a number of ways to gain experience in data science no matter your skill level.
Several universities now offer both undergraduate and graduate degrees in data science. If a master’s degree in particular piques your interest, Fortune ranks the top in-person and online programs in data science. Plus, schools are increasingly offering certificate programs or partnering with bootcamps. The latter, regardless of affiliation, may offer cheaper and quicker pathways to earn hard data scientist skills.
Many top tech companies like Cisco, Salesforce, and Google as well as Microsoft, Amazon, and IBM offer training programs for users to learn skills under data science’s umbrella—whether that’s focused more broadly on things like data analysis or more defined skills like Python and machine learning.
But regardless, Fagen-Ulmschneider says the most important thing for those interested in getting started in data science is to start working on a project that will not only help you learn but also build a portfolio.
“Literally, you can just start working right now,” he says.