As time goes on, and the IT-centered job market becomes more and more competitive, there’s an increasing amount of people looking for ways of getting into the industry as fast as possible. Questions on how to become a data scientist and how to score a job in the IT industry are quite popular among people who want to get from point A to B ASAP. If you’re interested in becoming a data scientist and want to know all of the different requirements that you’ll have to meet – great! You’ve come to the right place!
For starters, we are going to talk a bit about the profession of a data scientist itself. You probably already know the general information about this specialty (since you are looking for how to become a data scientist), but a quick rundown will serve as a great memory refresh. After that, we’ll get into the main requirement that you’ll have to meet in order to start your journey towards the data scientist career path. Finally, I’ll tell you some of the main reasons why people might want to learn how to be a data scientist, in the first place.
Table of Contents
Before we actually get into the tutorial and start talking about how to become a data scientist, let’s lay down some of the basics surrounding the profession. If you’re still contemplating whether or not this is the career path for you, this brief introduction might sway your decision into one or the other direction. And honestly, though, it would be odd to start talking about becoming a data scientist without first establishing what this person does, now wouldn’t it?
“Data science” is actually an umbrella term. While it is a career path, there are multiple different “branches” that you might want to choose, depending on your own skills and preferences. If we were to define the term itself, data science is concerned with the gathering and analysis of huge chunks of data. These types of scientists usually work in huge corporations that handle vast amounts of data every single day – data scientists are responsible for the “translation” of the incoming data (numbers) into understandable, everyday English.
There are two popular branches of data science that a person looking at how to become a data scientist should know – data analytics and data engineering. Data analysts interpret the data that is presented in front of them and then bring the results back to their employers. Data engineers do the same thing – however, they must also gather the data AND, after they finish analyzing it, come up with a “plan of action” that would be based on the results of their interpretation.
Needless to say, this is a super TL;DR version of the career path, but you should be able to develop a general idea. Now, to continue our “how to become data scientist” tutorial, let’s jump straight into the requirements themselves.
How to Become a Data Scientist?
When you’re looking for information on how to become a data scientist, there are three main things you need to keep in mind – education, motivation, and experience. If all three of them are in place, you can be certain that you’re on the right path of becoming a data scientist. With that said, let’s take a closer look at each of these points.
Proper education is probably one of the most important points when you’re thinking about the data scientist career path. And this doesn’t necessarily only concern traditional education, either! More and more people every single year are moving away from traditional, formal education institutions and are choosing to learn online. Whether that’s a good or a bad thing is still unknown, but one thing’s for certain – employers now are much more fluid in hiring people that don’t possess any form of traditional education but have acquired their knowledge in some other way. Online courses, articles, tutorials, YouTube videos – the list goes on forever!
Whatever your choice of receiving proper education might be, it is still important to have one. The very first thing that you need to do is make sure that such fields like math, computer science and IT, in general, are “in-line” with your hobbies and interests. As a data scientist, you will spend a lot of time working on and with various amounts of technical data and numbers – better make sure that it’s your cup of tea!
After that’s all said and done, your best bet is to enroll (or get accepted) into a field that would be closely related to data science – a bachelor’s degree in computer science, physics, maths or any other similar field will do fine. Now, this is probably more of a “motivation-based” point, but do keep in mind that you have to display good results from the very beginning of your studies in order to be able to score the data scientist career path. It’s a difficult profession that requires a lot of concentration and doesn’t have a lot of space for error – if you work hard from day one of your studies, you’ll increase your chance of actually getting the job afterward, and becoming a true professional in the field.
After you receive your bachelor’s degree, the next step in how to become a data scientist is also pretty self-explanatory – time to go for that master’s degree! Yup, I’m serious – let me elaborate.
You may or may not know, but you’re not going to be able to surprise anyone with a bachelor’s certificate in the 21st century. These days, having a master’s degree is almost essential in order to be able to even compete in the job market of some of the more sought-after career paths – data science is no exception.
That being said, if you chose to skip traditional education altogether and just focus on individual learning – don’t worry! While it may be more difficult to get hired, and the question of “how to become a data scientist” might linger a bit more frequently in your Google search bar, you should still eventually get a job in the field. The only true criteria are for you to be a hard worker that’s also passionate about what he or she does. Which segways into our next point of discussion in this “how to become a data scientist” tutorial – motivation.
Although this might seem rather arbitrary and abstract at first, motivation is often the deciding factor between you getting the jo, or flunking it completely. Let me give you an example.
Let’s just say that you are competing for a data science job with another person. You both have the proper education, and are of a similar skill level – and you also both want that specific job. Let’s just say that you’ve had a rough week – your car broke down, your pet has come down with the flu, and there are taxes to be paid. All of these things result in you being able to show your skills in the job interview but also coming off as very unmotivated.
That being said, the other person came into the job interview like there’s no tomorrow – they wouldn’t stop talking about their passion for the job, how they want to integrate data science into their everyday lives, what different projects they have already thought about, etc. All of these things add up! Now, tell me – as an employer, which of these two people would you hire? That’s right – the motivated one!
Motivation isn’t only being a “happy-go-lucky” person that talks about their passion a lot. Actions do speak louder than words! If you’re trying to figure out how to become a data scientist, one thing that you should always keep in mind is that motivation doesn’t start and end with the job interview – your potential employers have to see that you already “live” as a data scientist and that you are keen on constantly improving your skills.
Finally, if you want to know how to be a data scientist, you should know that a little bit of experience will go a long way. Now, you might think – but what if I’m fresh out of college, and am looking for my first job? Well, to that I say – there are many different ways that you can acquire experience – an official, stable job is just one of them!
Many people are used to associating the term “experience” with the concept of a “job”. That’s doesn’t always have to be the case! You may earn experience with university or college courses, individual projects and simply working on your skills with data science every single day. Surely, most employers expect you to provide them with specific results, so it will definitely be beneficial that, while you’re looking for how to become a data scientist, you also spend a good portion of time researching some activities that would also provide certifications or other proof of your time spent doing them.
One thing’s for certain, though – no matter how much time you spend looking for how to become data scientist if you need to also constantly look for different ways to acquire experience.
Why Become a Data Scientist?
So, by now we have covered all of the main criteria that you would need to meet in order to score a job as a data analyst or engineer. However, there’s one more thing that we haven’t touched upon – the reasons why anyone would want to know how to become a data scientist.
Even though every single person that wants to get into the field of data science has their own reason to do so, there are some general things that could, quite possibly, be applicable to everyone. First of all, data science can guarantee a stable career path with plenty of opportunities to grow and further develop your skills. This is a super important feature for most people out there – if you’re looking for a stable job, you probably want to dedicate yourself to it long-term, and also have an opportunity to keep on learning and growing in the field that you specialize in.
Another huge reason for choosing data science is the salary. There’s a huge amount of people that want to know how to be a data scientist simply because they want to earn the salary of one.
Glassdoor.com estimates that the average annual salary that a data scientist can expect to earn should revolve around the $117,350 USD mark. This would come out to almost $9780 USD per month! That’s an amazing salary!
Naturally, the salary that you might make as a data scientist will vary. It all depends on the specific career branch that you might choose, your experience and skill level with data science in general, your geographic residence, an so on. Having said that, it is quite evident that the data scientist salary is definitely something worth working towards!
So – we have reached the end of this “how to become a data scientist” tutorial. Up to this point, we’ve talked about the actual profession of data science (and some of the main branches related to it), the most commonly referenced requirements that are essential for becoming a professional data scientist, and we’ve also covered the most appealing reasons for why people are interested in this profession, in the first place.
If there’s one thing to take away from this tutorial on how to become a data scientist, it’s that this career path requires a lot of hard work and dedication. Whether you’ve just started learning all of the tropes of what it has to offer, or you’re already an experienced data scientist who just needed a little bit of motivation, remember – as long as you work hard and have a clear and strict work etiquette, you shouldn’t encounter any problems whatsoever.
All in all, I hope that this tutorial was useful to you and that you now know how to become a data scientist, and why you should do so, in the first place. If you do decide to go for it, I wish you the best of luck in your future career path!