Becoming a Data Scientist Without a Degree

Data science continues to be one of the fastest growing fields across multiple industries. Every business needs accurate data to target the right customers, manage supply chains, make decisions about new products, and much more. But did you know that you can become a data scientist without a bachelor’s degree? Read on to see how you can be on your way to landing an entry-level data analysis role, fast.

What is data science?

Data science is the work of ensuring that data is clean, timely, and accurate in order to extract insights from it. Those insights drive critical business decisions. From tech, to retail, to healthcare, data analysis can solve a huge range of problems. That’s why data scientists continue to be in demand.

Data scientists_{What Do Data Scientists Do?} use programming skills, mathematical knowledge, and business savvy to identify patterns and trends in data. They clean up data, perform data analysis, write algorithms, create data visualizations and narratives, and report findings to colleagues and company leaders. 

How to become a data scientist without a degree

Start with an online data science bootcamp

Can you really get a data science job without a degree? Yes! In fact, you could probably teach yourself a lot of the fundamental data science skills, like the Python programming language. But the right bootcamp_{Review Platforms And Rankings Worth Your Attention When Choosing a Bootcamp} can help you home in on the right tools and languages, answer your questions in real time, offer peer support, and provide structure and accountability. As TripleTen grad Rachelle_{From Tourism Sales to Data Science at Spotify: TripleTen Grad Rachelle Perez Lands a Career in Tech} recalls, “Being able to talk with professionals quickly became my favorite part of the learning. Once you do that over and over again, it becomes more of a two-way communication".

So, those code reviews became a way to show that I was actually progressing. Rachelle, TripleTen grad

Invest time in learning and practice

The right bootcamp will ensure you’re learning the right skills for the job. But it’s critical to spend time applying those skills before you look for your first full-time role. One way to do that is through externships_{Why Externships Are Great for Your Portfolio}. Externships are similar to internships: they mimic the real-life tasks of companies and provide actual assignments, like helping build an app. Their goal is to bridge the gap between an academic environment and projects at real companies. While not required as part of the bootcamp, they can help you build out both your resume and portfolio while getting a feel for the day-to-day work of a data scientist.

Build a strong portfolio

In addition to an effective resume, a portfolio is key to making you stand out as a candidate. A resume lists your work history, but a portfolio shows off how you apply your skills_{9 Steps to Create an Effective Data Science Portfolio}. A portfolio can showcase school assignments, pro bono work, or hobby projects — it doesn’t have to be paid work. But it should show your skills in action. Pick your favorite projects, then write a reflection on the problem, how you solved it, and why you chose to solve it in that particular way. Then, add a link to your portfolio on your resume and in your LinkedIn profile.

Connect and network

Now that you’ve learned new skills, and you’ve showcased them in a portfolio, you’re ready to start looking for work. But don’t focus all your energy just on filling out online applications. Start making personal connections, too. You can go to conferences, local meetups, or talk to friends of friends. When she started looking for full-time work, TripleTen grad Yuliya_{From Chemical Engineering to Motherhood to Tech : Yuliya Khilko’s TripleTen Story} reflects: “I tried to be present everywhere — I joined Facebook and LinkedIn groups, looked for opportunities, messaged my friends who worked at startups.” Eventually, she got a recruiter message and was hired at lululemon, most likely because her “activity made [her] profile more visible to other people.” And since many tech companies offer referral bonuses, it never hurts to ask a connection to recommend you for an open role.

Volunteer or participate in competitions

You don’t have to be a pro to enter a competition: there is wide variety out there for every skill level! Prioritize competitions where you enjoy the challenge over the ones you think you can win. Try looking on platforms like Kaggle and DrivenData to find the right events. Not only can you win prizes and enhance your portfolio, you can also have a real impact on fields from education to climate change mitigation. 

Another way to build out your portfolio and expertise is to offer up your skills for free. Sites like Datakind and Catchafire connect data scientists with nonprofits who need help. Don’t forget to ask for a LinkedIn recommendation when you complete a project.

How long does it take to become a data scientist?

The great news is that you don’t need a computer science degree to become a data scientist. TripleTen’s data science bootcamp_{What’s Included in TripleTen’s Data Science Bootcamp?} takes 8 months, part time. Even if you add in extra time to work on additional projects and hone your skills, you could still find a data science job in under a year.

Real success stories of our graduates who became data scientists

Wondering how other TripleTen grads became data scientists without a traditional degree? Here are two stories to inspire you:

How Gor leveled up to a dream role at Amazon

After Gor_{Changing His Career, Not His Company: Gor Mikayelyan’s TripleTen Story} landed a logistics analyst role at Amazon, he was thrilled to be at his dream company, but the role didn’t excite him. He wanted to do more with data, so he set out to learn Python on his own. But, he says, “after learning Python for a few months, I realized I wasn't going fast enough and I wasn't learning as much as I wanted. That's when I decided to join a bootcamp.” The bootcamp structure kept him motivated, and in-depth conversations with instructors helped him truly master the material. Upon completing the bootcamp, Gor landed a data analyst role at Amazon: finally, a dream role to match his dream company.

How Rachelle went from tourism sales to Spotify

When Rachelle_{From Tourism Sales to Data Science at Spotify: TripleTen Grad Rachelle Perez Lands a Career in Tech} was laid off from her role in tourism sales, she decided she might as well try something new. She was already interested in data, and a 6-month bootcamp landed her an entry-level job in the field. But she needed to level up if she was serious about her new career path. That’s when she found TripleTen. She was surprised by the rigor of the bootcamp, but was grateful for the active support. And the rigor is what helped her land her next role as a data analyst at Spotify. The job is satisfying, and it came with a huge bonus: “I’m happy with the culture. I actually probably put in less hours now than I ever did in my older jobs. I spend much more time with my son now,” says Rachelle.

Become a data scientist with TripleTen

Data science continues to be a great career bet: the U.S. Bureau of Labor Statistics is projecting a 35% increase in data scientist jobs in the next 10 years! If you’re thinking about making a switch to this career path, TripleTen can offer you the right support, from bootcamp to job search. Find out if our part-time Data Science Bootcamp is right for you.