Data Scientist without a degree?! 7 paths for investing sweat-equity to get the data science job // Data science continues to be one of the hottest careers on the planet, and for good reason. It’s a challenging, innovative, and well-paid career that lures many aspiring enthusiasts. The field of data science is still evolving and jobs will continue to grow over the next decade. To work in data science requires a very specific set of skills, but does it require a degree?

Can you become a Data Scientist without a degree?

Not necessarily. To apply for a job as a data scientist, there’s no doubt that a degree is an advantage, especially if you have a master’s degree in data science. However, one can follow the self-taught route, a good option if you plan to start your own data science business. Clients are more interested in your skills than a degree.

If you are interested in a career in data science, here’s how to break into the industry without a degree.

How to become a data scientist without a formal degree

While there are obvious benefits to getting a degree in data science, it’s entirely possible to learn data science yourself. If you’re a self-starter and self-motivated, you can pursue your goal of becoming a data scientist by taking the following steps.

1. Determine your level of aptitude for maths, statistics, and computer science

I’m guessing you have always been somewhat of a computer or maths geek, hence your interest in becoming a data scientist. If you’re naturally gifted with these skills, you have a good foundation to further your knowledge and skills in data science. If you’re not as confident in your skills, formal studies may be a better option.

2. Get to grips with the fundamentals of data science

At its simplest definition, data science is a field that involves collecting, analyzing, and interpreting large volumes of data. It is, however, a complex job with many different layers to it. You’ll need to understand the fundamentals of data science that includes:

  • Software engineering and data architecture.
  • Data mining, cleaning and visualization.
  • Mathematics like linear algebra, linear regression, and probability theory.
  • Artificial intelligence and machine learning algorithms.
  • Statistics and data analytics.

There are plenty of resources and online courses to gain knowledge in the specialty of your choosing. I’ve put together a list of online training courses in data science, data engineering, and data analytics for both beginners and more advanced data professionals.

here are 6 ways to become a become a Data Scientist without a degree3. Learn programming

To become a data scientist, you have to learn a programming language. The most common programming languages are Python, SQL and R. These three are highly recommended if you want to work in data science, but there are other popular languages like Java, Scala, and Julia.

There are hundreds of courses online that teach programming languages at a fraction of the cost of a data science degree. Once you speak the data science language, you’re poised to move forward with your goal to work in the field.

4. Get hands on experience

Once you’ve laid the groundwork by educating yourself in data science, it’s time to put your knowledge into practice. Ultimately, it’s your work that will prove you’ve got what it takes to be a successful data scientist.

Find projects to work on and start building a portfolio. If you can’t find a real-world project, create one yourself. The possibilities are endless — predict who will win the next election, whether an upcoming movie will be a box office hit, or create an algorithm that can spot fake news.

5. Participate in data science competitions

Another great, and fun, way to practice your data science skills is by taking part in competitions. You’ll get to exercise your creativity, gain exposure, and receive feedback on your projects. It’s a great way to test your skills and uncover weaknesses.

Kaggle is a popular data science community that runs competitions, some of which offer some incredible cash prizes. Kaggle has a thriving community that discusses ideas and shares open-source code with another.

6. Enroll in a data science bootcamp

Bootcamps are designed to prepare candidates for placement in entry-level data science jobs. You’ll be put through an intensive career training program that covers data, algorithms, machine learning, data analytics, and programming languages.

When you’re a newbie looking for your first data science job, you’ll be up against degreed graduates and more experienced candidates. A bootcamp program can help prepare you for the job hunting process. Many offer career coaching, guidance on finding a suitable job placement, and assistance with job applications. Some will even take you through a mock interview.

Many successful data scientists are self-taught. That doesn’t mean a formal degree in data science doesn’t have its merits. It’s a good stepping stone in acquiring the skills you need to enter the job market. If, however, you’re not keen on going back to school or tuition fees are out of your reach, going the self-taught route is a viable option.

Lillian Pierson, P.E.

Lillian Pierson is a CEO & data leader that supports data professionals to evolve into world-class leaders & entrepreneurs. To date, she’s helped educate over 1.3 million data professionals on AI and data science. Lillian has authored 6 data books with Wiley & Sons Publishers as well as 8 data courses with LinkedIn Learning. She’s supported a wide variety of organizations across the globe, from the United Nations and National Geographic, to Ericsson and Saudi Aramco, and everything in between. She is a licensed Professional Engineer, in good standing. She’s been a technical consultant since 2007 and a data business mentor since 2018. She occasionally volunteers her expertise in global summits and forums on data privacy and ethics.

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