“Old data scientists never die–they just get broken down by age.”
You might think data science is a young person’s game. After all, this is a relatively new discipline that might not have been around when you were in school. But research shows nearly half of all data scientists are 40 years and older—over twice the number of professionals aged 20-30. Considering that the Harvard Business Review didn’t name data science as the “sexiest job of the 21st century” until 2012, we can assume that many of these over-40s started their careers slightly later in life.
Whatever your age, it’s never too late to pursue your dreams of becoming a qualified data scientist. Learn how to succeed in this profession below.
There’s No Conventional Route to Data Science
We’re told that the most common route to a data science career is enrolling in a STEM degree program after high school, earning a data science master’s degree and landing an entry-level job after graduation. However, this is just one way to become a data scientist. There are multiple paths into data science that you might not even know about. Enrolling in data science bootcamp, for example, will hone your skills and move you one step closer to achieving your goals.
Think about the one thing all the best data scientists have in common: They know their craft! These professionals have learned how to:
- Determine data sets and variables
- Process large data sets
- Generate insights from data
- Write complex code
- Draw insights from data
- Manipulate different databases
- Work with statistical models
- Research even more complex algorithms
But there’s no time limit for learning these skills.
Whether you’re 21 or 71, you can learn the intricacies of data science and, with enough expertise and a great portfolio, land a well-paid job.
If you have some basic data science skills, you’re already on your way to becoming a professional. Know how to program with Microsoft’s famous spreadsheet software? You’ll Excel in your field! Never let your age stop you from doing what you want to do.
How to Change Your Career to Data Science
Perhaps you’ve never worked in a data science environment and have little experience. That’s OK, too. Data science is still one of the fastest-growing industries in the world and businesses are looking for talented pros to help them get more value from their data. Once you have skills and experience, employers won’t care that you had an entirely different career before becoming a data scientist. Plus, you might even be able to transfer your talents to data science.
Say you currently work as a marketer. At first glance, this job seems completely unrelated to data science. But you probably have experience analyzing data sets of some kind and generating business intelligence. You can easily transfer those skills to data science!
Switching from one career to another is daunting at any age. The fear of the unknown might be holding you back. What if you don’t get a high-paying job? What if you’re not good at data science? It’s important to note that many people have these doubts, even those 10, 20, 30, or 40 years younger than you or more. Would-be data scientists pursue this career because they have a passion for analytics and solving complex problems.
That passion doesn’t disappear with age.
Overcoming Challenges of Breaking into Data Science Later in Life
Research from the University of Gothenburg shows that ageism is common in the tech industry, with tech workers over the age of 35 considered “too old.” Don’t let these ridiculous prejudices deter you from realizing your dreams. Some of the world’s most successful data scientists are older. Take Yann LeCun, for example, one of the most famous data scientists of our time. Now Director of AI Research at Facebook, Yann created convolutional neural networks (CNN), which helped develop deep learning.
There might be some skills required for data science you wished you learned earlier in life. For example, a deeper understanding of statistical analysis. But nothing is stopping you from learning these skills right now, no matter your age. There are more resources out there than ever before that will help you develop your skillset and turn you into a more proficient data scientist.
Age might be a variable in data analysis, but it’s just a number when it comes to your data science career. There are many routes into this profession and you can land the job of your dreams by developing experience and gaining an incredible skillset. Start your career in data science now—before it really is too late!