What do the words “data science” make you think of?
Some may think of someone in a white coat crunching numbers all day. But if you’re like me, you probably just stare.
Once hailed as the “Sexiest Job of the 21st Century” by Harvard Business Review, the profession is still undergoing changes as the demand for data science skills continues to grow. You see, much like a funeral director has an endless supply of clients, companies have an endless need for people who can gain insights from data— because data is ongoing, like the Energizer BunnyTM!
What a data scientist does on a daily basis can largely be a function of who they work for and how big or far along the company is. Their tasks may range from data collection and cleaning analytics to testing or using algorithms and even using artificial intelligence (AI). Regardless of where the data scientist sits on the professional spectrum, the core function of data scientists is to solve real-world problems using data.
In K-12 education, data science instruction equips students with the introductory skills and problem-solving strategies that are critical for collecting, analyzing, interpreting and visualizing data. It focuses on processes and techniques rooted in mathematics, statistics and computer science, all of which help prepare students for more advanced data science skill development when they enter college or the workforce.
While the study of data science is typically a college pursuit, and typically that means an advanced degree, there’s a great case to be made that introductory data science skills can, and should, be taught in K-12. If we wait for students to earn advanced degrees, the number of people who can use data science skills is going to remain undoubtedly low and, even more concerning, fail to keep up with workplace demand. And while the volume of data is expanding like crazy, the number of people who can draw insights from that data is not.
The fact is data science skills aren’t going away. If anything, they’re only expanding to be needed in more and more jobs in diverse industries that we don’t typically think of when discussing data science.
A new report from ExcelinEd and the Burning Glass Institute showcases how pressing the need is—and what states can do to better prepare students for future employment across job sectors.
The Burning Glass Institute’s analysis of U.S. job postings offers a clearer understanding of the demand for key data science skills. It helps answer the question: What do workers need to succeed in critical roles throughout the U.S. economy?
Here are a few key takeaways:
Washington (28.1%), California (27.3%), and Virginia (25.8%) lead the way in terms of job posting demand for data science skills. Arkansas (23.4%) and Iowa (22.5%) may be a bit surprising for folks who don’t live in those states. Even in the states where demand was lowest—Mississippi (17.6%), North Dakota (16.3%) and Vermont (15.3%)—the percentage of job postings still asking for data science skills is arguably high.
While jobs requiring sophisticated data science skills offer the largest bump in pay—data strategy and machine learning (14%) and artificial intelligence, data architecture, and big data (12%)—even basic, broad-based data science skills, such as data visualization, data processing and data cleaning, tend to offer meaningful pay increases.
The report also shows that demand for data science skills is increasingly spreading to industries beyond the tech world. Between a quarter and a third of job postings in manufacturing, trade, oil and gas, agriculture and transportation are seeking workers with various data science skills. Increasingly, jobs like medical records specialists and public relations specialists require some degree of data science skills.
If a single, overarching message is to be found here, it is that data science is indeed for everyone! Education leaders, policymakers, and employers have good reason to share a common interest in preparing American workers with the data skills they need to thrive in today’s workforce.
Most schools today don’t offer formal data science training, and data science skills remain sparsely represented in student learning standards. It gets even worse.
The most recent National Assessment of Educational Progress (NAEP) shows student scores in the fundamentals of data-related skills have been declining greater than any other math content area. Notably, this decline existed before COVID affected student progress.
So how can state policymakers ensure data science is available to students in K-12 schools and that what they’re learning aligns with data science-related jobs? Here are four reasonable and realistically attainable policy solutions:
A few states are ahead of the curve when it comes to incorporating data science into K-12:
For a deeper dive into what the data science-related jobs landscape looks like in your state, please visit ExcelinEd’s Data Science resources and check out the interactive map.
