“Data science doesn’t care about what you majored in or if you even got a degree. It’s what you do with data that matters,” says DJ Patil, an American mathematician, computer scientist, and the man who built the first data science team at LinkedIn.
While thinking about grabbing a data scientist job without a degree or whether such a thing is even conceivable, it’s best to seek guidance from the greatest minds.
DJ Patil along with Jeff Hammerbacher, a data scientist and formerly chief scientist and co-founder at Cloudera were the first to coin the modern version of the term “data scientist” in 2008.
In late 2016, Patil on his tweet said, data science couldn’t care less whether you’ve earned a Bachelor’s degree or even got a degree. However, it is what you do with the data that matters. Off late, the data science offers the individual unique and multiple job roles to choose from. He followed up and said, HR managers and employers should take note – judge people by their work and not education.
The data scientist role is diverse thus skills required in this field vary widely. For instance, as a data analyst, you need different skills, likewise, a data architect requires a different skillset and a statistician.
A bachelor’s degree is not mandatory to become a data scientist
As overwhelming as it sounds, becoming a data scientist professional without a bachelor’s degree may sound like a cakewalk. You need to keep in mind, it is an uphill battle. Focusing on the individual’s experience rather than an education makes perfect sense.
If you dig deeper, you will find many data scientist professionals and leaders across the globe do not possess technical degrees, yet today they’ve become influential data scientists. For instance, Doug Cutting, the man known to create the Hadoop framework has a bachelor’s degree in linguistics. Tim O’Reilly, the man behind O’Reilly Media, a company famous for the world’s publisher of data and programming resources possess a bachelor’s degree in the classics.
Let’s get real.
Earning a degree does help, however, it is not mandatory. Companies are more focused on data science skills rather than degrees. Most of the job openings in data science does not even mention having a bachelor’s degree as a prerequisite.
Owing to the demand for skilled data scientists and lack of supply, most companies are even willing to hire individuals who are highly skilled in data science.
However, to get into a data analyst role, the individual requires an undergraduate degree in subjects like – science, mathematics, technology, and engineering. In addition to this, having experience in programming, predictive analytics, and computer modeling is an add-on advantage.
The industry does have a strong affinity toward candidates with degrees.
But according to the current industry demand, it is not mandatory. You can still become a data scientist professional even without a bachelor’s degree.
Now, here’s the deal. You may not need a bachelor’s degree, but you do need the skills. To earn data science skills, you need to be exceptionally good with mathematics, statistics, programming, and business acumen.
How can you improve your data science skills?
Seeking a career in data science without a degree can be challenging, here’s what you need to focus upon.
If you delve deeper, you will find multiple online learning programs and data science certification programs for aspiring data science professionals. However, you need to be specific in choosing the best data scientist certification program that best suits your profile. For instance, you will find multiple certification programs that offer programs only for working professionals and freshers.
R and Python programming is crucial for tech professionals looking to get into the data science field. Python is ideally used for general purposes in data science and R is used to solve statistical problems. It is said, 90 percent of data scientists know Python. As a beginner in a data science career, learning Python is recommended because it is simple and easy to learn.
Further on, you can start practicing your programming skills on open source platforms such as GitHub and perhaps start solving simple datasets through Kaggle. GitHub is one reliable platform where most developers code, practice, and upgrade their learning skills.
Once you’ve acquired the above skills, you can start working on simple dataset projects. You will find many free datasets available online, if not, Kaggle, as mentioned is a great platform to get started with your data science projects.
Seek help from peers from the industry, and start building your portfolio. Staying connected with your peers could help you through the interview process. Since they’re in the industry, they can easily guide you through the type of questions that most hiring managers generally ask. Moreover, they can take your mock interviews keeping you steady and confident with the skills you’ve acquired.
To find out a difference between data analyst and data scientist you can check out this article.