Should you get a master's degree in data science?

I recently heard about Betteridge’s law of headlines. It states that if an article has a question as a title, the answer will always be no. It is, of course, a humorous law and not an actual one. Still, the rebel in me couldn't miss the opportunity to contradict a law. And so, the answer to this headline is a shiny "it depends". I'm sure you didn't see that coming.

The question of whether you should get a master's degree or not is very personal. It will depend on personal preferences, learning style and career goal. That's why I think it's ineffective to try to find an answer to it online. Though it is still one of the most frequently asked questions on Quora.

In this article, I will not list arguments for or against getting a master's in data science. Instead, I will give you pointers on what to consider when making this decision.

Keep in mind that I formulated these criteria with the assumption that you want to work as a data scientist in a commercial company after this degree. It might not apply to you if you want to stay in academia.

Here is what I think you should consider:

Not all degrees are created equal

Data science is a popular topic and several data science degrees are popping up every day. Make sure the education that you’re getting will be of adequate quality. It’s not the name of the degree that counts at the end. It’s the education. The best way to check the education quality is to check the instructors and the curriculum. Try to answer the questions:

• Are the instructors respected scholars? As in are they contributing to the academia, are they active researchers or are they still stuck in the technology of 10 years ago?
• Is the curriculum adequate? Of course to answer this question you need to have a general idea of what data science is and what the required skills are. I know you’d probably want to believe that the school has thought about it and created a complete and flawless curriculum but you should check anyway. Make a list of skills that you absolutely want to learn and cross-check it with what the school offers. It’s better to be cautious than spend your two years not learning exactly what you wanted to learn.
• Is the degree hands-on enough? This is the hardest question to answer of all. One way to figure out if the degree is too technical and does not give enough importance to practical skills is by asking former or current students. You can find them on LinkedIn or in your network of friends.

The name of your school might matter

Related to the previous point, if there are many schools offering a degree with the same name, considering everything else is the same between two candidates, the prestige of a school might matter on a hiring decision. This is not to say that don't ever take a master's degree from a non-prestigious school. What I mean is, evaluate every degree with its own merit. Simply put, if a data science degree from the top university of your country is adding 10 merit points to your profile in your future employer's eyes, a degree from a less popular/well-known school might add only 5. Make sure when you plan your path, take this into consideration.

Getting a data science job is much more than the technical knowledge

Companies look for competent people who can deal with real-life challenges and adapt quickly. Having a relevant degree might not be effective enough if that’s all you're bringing to the table. The company you’re applying to might still go with someone who doesn’t have a degree but can display their competence better. The relevant competence can be inter-personal skills, projects they worked on, domain experience, etc.

Every company has different priorities

If you are looking to apply to a specific company/industry, I’d say make sure to understand their requirements before investing in a master’s degree. Maybe they’re fine taking you in with only basic knowledge and teaching you on the way.

Why are you doing this?

Make sure to understand why you're considering a master's degree. Is it because you did some research and you are convinced that it will be beneficial for your career or is it because you've heard from people on the internet that it's a must in order to get a data science job? Do the right thing for yourself, not the common thing. Starting a data science degree just because you're not sure what else to do can prove to be unproductive.

It is a big decision after all to invest money and time on an official degree. For some people it will be a great match and for some it could be an unnecessary distraction. The gist of what I'm trying to say is: it is always a plus to have a relevant official degree in your resume but you have to compare the benefits to the cost of your life and decide if it's wort it. No one else can make this decision for you.

I hope this helps clarify some of the important things you should keep in mind when making this decision. Good luck!