4 Steps the Data Science Industry Is Taking to Appeal to a New Generation of Scientists 4 Steps the Data Science Industry Is Taking to Appeal to a New Generation of Scientists
Data science is one of the fastest-growing industries in the nation, with job opportunities expected to expand by an impressive 22%... 4 Steps the Data Science Industry Is Taking to Appeal to a New Generation of Scientists

Data science is one of the fastest-growing industries in the nation, with job opportunities expected to expand by an impressive 22% over the next 10 years. It is already part of almost every mainstream industry and will become more critical and valuable in the years and decades ahead.

Finding qualified talent and attracting more young people to the data science industry will be crucial for keeping up with that growth. There are several exciting steps that the industry is taking to make it happen, with education at the heart of it all.

1. Girls Who Code

Women are drastically underrepresented in computer science fields. This means millions of talented women are out there who could be the key to meeting the increasing demand for smart and capable new hires. All the data science industry has to do is equip them with the tools and support they need to get excited about data and coding. Girls Who Code starts that process at a young age, empowering girls as young as 8 years old to get involved in computer science. 

Programs like this are far more than niche initiatives. Girls Who Code found that its alumni are 15 times more likely to pursue computer science-related careers. That is a monumental impact, especially considering that women make up only 27% of the STEM workforce, with numbers trending down in computer science fields in particular. 

Considering that women also make up half the U.S. workforce and kids are only getting more interested in technology, investing in data science education for women could revolutionize the industry.


2. STEM Tools for Kids

Gen Z students love using technology for learning, with 81% saying tech improves their grades and 84% saying it boosts their overall educational experience. 

The data science industry should tap into this rising generation of tech-savvy young people by creating free, easy-to-access educational tools. For example, more than a thousand publishers for K-12 and higher education have already taken the initiative to offer digital books for students, including many publishers in the data science industry. Also, websites like the popular kids’ coding community Scratch make it fun for children to learn about computer science. 

Gamification is an especially effective tool. It allows kids to learn about coding and data by actively creating something fun and functional. This early interest can help encourage young people to pursue fields like computer science, data science, and software engineering in high school and college. 

Along with websites, educational toys and tools are of equal importance. The data science industry can create initiatives to get tablets or laptops to more students, allowing them access to valuable technology and all the learning resources that come with it.

Additionally, more companies are making toys that teach kids about coding and computers hands-on. For example, STEM toy company Kano makes kits and education tools that enable children to build their own computer and code it themselves. They even have a code-able Harry Potter wand. Toys like this are a hit with kids, and the data science industry could help develop more to keep that computer fun going.

3. Coding Bootcamps

One exciting movement taking hold in the STEM world is a changing attitude toward education requirements for people in computer science-related fields. Fewer employers require a four-year degree for coding and development positions. Instead, new hires are using “bootcamps” to get the experience and training they need quickly and for far less money than the typical cost of a college education.

Coding bootcamps don’t just cover the basics, either. Focused courses are widely available for data science, as well as cybersecurity, full-stack development, UI and UX development, and app development, among others. 

These programs can cost as little as a few hundred dollars for focused periods of intensive training, which can often be done remotely. This makes it easy for working people to change careers and switch to data science. Additionally, promoting bootcamp-style offerings more widely could lead to a surge in new talent entering the hiring pool, as young people realize what an affordable and valuable opportunity they are. 

To put this in perspective, the average cost of a four-year degree in the U.S. is over $35,000 per year. In comparison, even if a student were to choose one of the most expensive, top-rated coding bootcamps in the nation, they would still only spend $20,000 total and be done in a matter of 12 weeks. Bootcamps can provide an excellent return on investment since the average starting salary for entry-level coding professionals is over $50,000 a year. Many bootcamp programs are available for a few thousand dollars or less, so it is easy for prospective students to find something that fits their needs. Data science organizations can help by offering scholarships for specific programs.

For students looking for even more affordable options, the subscription-style online coding program Ai+ Training is available. This program is similar to coding bootcamps but takes a more self-paced approach, allowing students to choose individual topics they want to learn about and study those over however many months they like. What is particularly advantageous about these types of a la carte programs is that they allow students unlimited access to all of the program’s courses and resources through their monthly subscription, so students can essentially build their own custom bootcamp program.

Data science leaders and professionals can help support these programs by offering to speak at virtual events and provide consultation on new course curricula.

4. Open Source Resources

What the data science industry can take away from the demand for online coding programs is the need for more affordable access to educational resources. Things like free textbooks, open-source code libraries, and tutorials and courses enable students of any income level to pursue careers in computer science fields. Open-source coding and DIY tools have gained increasing popularity among the general public because they allow anyone with enough skill and curiosity to learn how to use the computer programs that run the world around them.

Open-source libraries are helpful for the industry at large, as well. Students, no matter how they are studying code, can get authoritative info to help them with projects, expanding on their learning in online or traditional courses. Seasoned professionals can use open-source libraries as well, though, to refer to new topics or get a refresher on old ones. These documentation libraries provide an even footing for everyone utilizing a certain programming language to get up-to-date information about syntax and process requirements.

It is important for data science professionals to remember that many of today’s kids are getting into coding initially using free, easily accessible resources, which then often lead them to explore coding bootcamps and conferences, online a la carte coding classes, or clubs like Girls Who Code, all of which will be vital for training the next generation of data and computer science experts.

Data Science for Everyone

If there is one thing Gen Z is passionate about, it is equality. This rising generation of young people has an intuitive understanding of technology, and that interest in tech is shared by people of all backgrounds and demographics. Extending opportunities for education is the best way for the data science industry to get this talented generation involved. The payoff could be a wave of skilled, qualified coders, engineers, and scientists lifting the whole world with innovations.

Editor’s note: Interested in staying up-to-date on all of the cutting-edge topics in data science, including how to implement data-driven approaches in your industry? By subscribing to our Ai+ Training Platform, you gain access to new workshops and training sessions every week, meaning you’re never stuck behind.

April Miller

April Miller

April Miller is a staff writer at ReHack Magazine who specializes in AI, machine learning while writing on topics across the technology sphere. You can find her work on ReHack.com and by following ReHack's Twitter page.