Four Steps to Break Into Data Science

Data Science professionals are in very high demand these days. The main reason is that every company in the market is looking for a way to extract valuable information for an abundance of data they collect each day. And, they need someone who knows how to do it right.

That said, becoming a data scientist may be more than the right choice when it comes to choosing a career path. For example, 28% more data science professionals are needed around the world this year alone.


By 2026, around 11 million jobs will be created in the field of data science. Not to mention that the salary for data science professionals may easily reach six figures. Therefore, if you’re wondering about becoming a data scientist, now is a really good time to start working on it. With that in mind, here are a few steps to break into data science.

How proficient must a data scientist be?

Truth be told, data science is a demanding profession. You need to be skilled and knowledgeable in various fields to be a successful data scientist.

As you might imagine, a lot of it has to do with math and computer science. However, don’t let this discourage you. You can learn everything you need to know as you go, and you will eventually end up enjoying it. That said, here are some of the areas of expertise a data scientist must be proficient at:

  • Artificial Intelligence (AI) proficiency
  • Machine learning
  • Deep Learning
  • Coding (Programming)
  • Mathematics
  • Statistics
  • Data Visualization
  • Computer Science
  • Communication

Aside from hard skills, it’s also beneficial to have some soft skills, as well. After all, you must be able to share and explain your findings with the rest of the team who, in most cases, will have absolutely no idea what you’re talking about. This is especially true when it comes to management and executives.

Therefore, a bit of business know-how and soft skills regarding communication will come in handy. Your knowledge can make sense of big data, which is what businesses are after.

How to become a data scientist?

Unfortunately, there’s no clear path you can take to become a data scientist. After all, this is a relatively new profession in the market. What that means is that you’ll have to take one step at a time until you acquire enough skills and knowledge to kick start your career.

It’s important to note that a masters degree or even a PhD are welcome but not always necessary to pave your way into data science. If you happen to have a masters degree or PhD in one of the fields, such as computer science, physical science, natural sciences, math, statistics and so on, you’re already half-way there.

If you don’t have any degrees, you’re still good to go, only the road may take a bit longer. Therefore, you’ll need to learn a few things before you can start your career. Such skills are pretty much technical and involve skills, such as Python, R, MySQL, NoSQL, analytics tools and so on.

Getting started

As mentioned before, you don’t need a degree if you don’t already have one. However, you’ll have to learn and keep learning until you have a bit of knowledge and skills under your belt. Fortunately enough, the Internet is a vast place filled with learning material and online courses you can partake in to learn what you need.

Therefore, it’s important to choose how to proceed. This means that you must choose whether to hit the classroom, study online or a bit of both. While you consider your options, a good way to start would be to attend a data science course online.

There, you can learn the ropes and work your way up. Getting certified is definitely a good start. In a lot of cases, you won’t need more than certification to start your data science career. Whether you want to improve more and learn new things for your sake and perhaps for the sake of finding better employment, is entirely up to you.

Launching your career

If you’re lucky, you’ll find a suitable job real quick. However, it’s always a good idea to gain some experience beforehand. Enriching your resume with projects and work experience can only benefit you in the long run. So, here are a few things you might consider doing before actually applying for a job in data science.

  • Attend data science seminars, webinars, conferences and events
  • Build a network of contacts and join meet-up groups
  • Volunteer on open source projects for a while
  • Look for an internship with one of the companies of your choosing

Honing your skills and working in the field a bit will help you grow. As you may already know, it’s always better to test your skills in a controlled environment before you take on any position, not just data science.

Not only will it boost your confidence, but any experience can contribute to finding an ideal job, not just any job. No matter how sought-after data science professionals may be, you might want to take the time to consider employment options until you find something that suits you the best.

Data science, although relatively new, quickly became a highly sought-after profession in the business world. With the market being so competitive, businesses rely on information data scientists can extract to gain a competitive edge and outrun their competitors. If you’re looking to become a data scientist, the journey will be difficult but also very rewarding, in the end.