The world’s leading publication for data science, AI, and ML professionals.

Do I Need A Degree To Land A Job In Data Science?

Exploring The Necessity of A Degree When Data Science Job Hunting

Photo by MD Duran on Unsplash
Photo by MD Duran on Unsplash

The easy answer to this question is simply No! There are numerous people that are working in Data Science that have no academic credentials to justify their role – I am one. However, as time has gone on, my strict stance against Bachelor’s degrees, Master’s degrees, and Ph.D. schemes has quite interestingly softened.

Well, sort of. I don’t find them completely useless now… I still believe focusing on somebody’s practical work experience triumphs over their Education to some extent, and even if we look at some of the greatest achievers in the tech space, many of them were dropouts – Mark Zuckerburg, Bill Gates, & Steve Jobs to name a few.

But I am not advising everyone that attends University in hopes of landing a role in Data Science should drop out. There are many benefits of completing a degree, for instance, it is a known fact that people that graduate from university earns more in their lifetime than someone that doesn’t go, also there are fundamental benefits you may gain like discipline and if you chose a technical degree (Science, Technology, Engineering, Math) you’d have deep fundamental knowledge in one of the key areas of Data Science.

"Instead, view your time in education as an opportunity to build a compelling network that will set you up appropriately for when you leave and beyond."

Essentially, being a Data Scientist requires a good knowledge of programming, mathematics, statistics & probability, and an understanding of the business sector. If you’re capable of displaying that you have these capabilities effectively then it’s likely going to triumph over the majority of certificates you can brag about. Therefore, to actively go about finding your first job as a Data Scientist, consider developing the following areas:

Programming Skills

The most commonly used programming languages for Data Science are Python and R. It is imperative you learn at least one of these tools in order to begin exploring data.

A controversial post on my LinkedIn Feed (Source: Alexander Freberg post)
A controversial post on my LinkedIn Feed (Source: Alexander Freberg post)

Data Scientists are split between which should be the programming Langauge of choice – with some being not so diplomatic in their disgust for the other language. I’ve sampled both and found that Python was much easier to learn and a lot more efficient. It also has more uses than Data Science which helps if you’re going to build your skills in other areas.

Math, Statistics & Probability

Simply stating "there is a chance the image is of a cat" isn’t as convincing as "there is an 80% chance the image is of a cat". That’s a rather dull example but you’d be expected to use statistics and probability to analyze and interpret any data you’re provided with.

Additionally, many of the algorithms you’d use to model data require a good understanding of different topics in math, such as linear algebra and calculus (as well as statistics and probability). It helps to understand what is going on under the hood of your algorithms for debugging purposes and for explainability in the event of an audit or if a customer wants to know why they were rejected for a loan.

Projects Portfolio

The idea that data is highly regarded as "the new oil", and every single person on the planet is generating tons of data is very important when thinking about Data Science. Data scientists would have to draw from the large complex data being generated and highlight the points that are beneficial for the business hence the need for domain expertise (this could be either the Data Scientist or someone on the team).

Regardless, you’re going to have to be able to prove that you can perform all of the tasks that you say you can perform so it helps to have a compelling portfolio that examines various problems and solutions to those problems.

Networking

The old adage "Your network is your net worth" is prominent in Data Science more than ever. At the end of the day, the field is new and there aren’t many metrics for distinguishing good practitioners from the rest unless you hire them and find out – which means a big risk in investment. Therefore, having someone that can vouch for you is quite useful when it comes to landing your first data science role.

Also, integrating yourself in the Data Science culture is a great place for developing and learning new things about Data Science as well as giving you a taste of what it is going to be like when you land your first job.

Wrap Up

I personally don’t believe it matters whether you have a degree or not when you decide to seek out roles as a Data Scientist. At the end of the day, the hiring company believes they have a problem that includes data and they require someone who is data-savvy to help them dig deeper into this problem in order for the company to advance – nowhere in that does it say a degree is required. However, there are necessary skills that you must be equipped with to do the work of a Data Scientist effectively but the internet has made it possible to learn many (if not all) of these skills online without having to get into debt.

Thanks for Reading!

Connect with me on LinkedIn and on Twitter for the latest updates.

Other Recent Post:

Data Scientists: Get Comfortable Being Stressed

Data Science: I Wonder If It’s Still Sexy In 2021


Related Articles