The world we’re living in is increasingly data-driven and is going to need people who can compile, analyze, and present it. Data scientists are needed virtually everywhere, and data science is one of the most promising and relevant fields anyone can enter at the moment.
You need to know, however, that the road to becoming a data scientist is not easy and you have to make sure that you have what it takes to make it. You also need to know what the job of a data scientist entails. Let’s take a look at some of the things you need to know before you embark on a career in analytics.
Simply put, the job of a data scientist is to use data to drive actionable goals. Data scientists will need to be able to pull data from different sources and create predictive models based on their findings. Having a degree in analytics is a great way to prepare for a career as a data scientist, but the role of an analyst is slightly different.
An analyst will also be responsible for collecting and analyzing data, but they won’t be as involved in the predictive modeling part as much. Data scientists are more problem-oriented and will use data to predict future possible issues. They will also start working more with algorithms and advanced computing.
Here are some of the tasks you will need to perform as a data scientist:
As you can see, the job of a data scientist is very extensive and specialized. This means that it takes a certain type of person to survive and thrive as one. While the job is very technical, you will need to have a good mix of soft and hard skills to succeed.
Critical thinking is one of the most important traits that you’ll need to have. Data scientists need to be able to rely on cold analysis first before passing judgments and formulating opinions. They need to be able to understand decisions being made or business problems and ‘model’ what is essential to solving that problem while tuning out any noise. This is probably the most crucial skill to have as a data scientist.
Data scientists need to be able to mute out their beliefs. Yes, they may rely on past experience, but they also know that intuition and experience aren’t perfect. Experience can be a valuable tool, but it can also become risky when we get too complacent. This is where blocking beliefs becomes important. It’s also not about looking at issues from the wide view of a novice, but being able to analyze a situation or problem from multiple angles at once.
Know that you will be heavily involved with coding, so if this is something you think you’ll struggle with, you’ll have a hard time as a data scientist. Before you become discouraged, however, we would suggest that you give Python a look. It’s one of the coding languages that has the lowest barrier to entry and is largely used in data analysis. You might find out that there’s a lot more copying and pasting involved than what you imagined, and once you start understanding basic principles, everything starts to come together.
Needless to say, that you’ll need to have advanced math skills. That’s non-negotiable. Unless you have skills with things like algebra, calculus, and algorithm, then you won’t be able to succeed. Data scientists have to compile massive amounts of data and create advanced statistical models that will influence key decisions. None of this is possible if you don’t have deep mathematical expertise.
The ability to communicate well is another very important, yet often overlooked skill for data scientists. The job of a data scientist doesn’t happen in a vacuum. The data they use needs to be presented and integrated by different sets of people who may not be as proficient as them. They need to be great at vulgarization. They also need to be able to squeeze out vital information from stakeholders.
Data science has a ‘story-telling’ component to it as you’ll have to present data in a way that seems actionable. You have to translate mathematical concepts into actual decisions. Data scientists who are poor communicators may cause employers to question the value of their role since they can’t intelligibly formulate solutions.
And last, but not least, you need to have the proper education. You can enter data science in a wide variety of ways; physics, mathematics, and engineering are all great majors to enter data science. Next, you can decide to move on to a master’s in data science if you feel you’re cut out for it.
If you want to learn more about whether you’re truly ready to become a data scientist, we strongly suggest you check out this page. You’ll learn more about what will be expected of you in your functions and the prerequisites to enter the data science master’s program.
Data science is an incredibly vast field, and you can fill positions in all sorts of sectors. You might be called to work with tech companies or any type of company trying to map their processes, or you might be asked to work with insurance companies. Data scientists play an essential role in evaluating risk, for instance, and help determine the cost of premiums among other things. Whether it’s healthcare, education, or even fields like sports and entertainment, there are positions for data analysts.
Another very lucrative field for data scientists is online marketing and eCommerce. eCommerce companies live on data, and those who have a strong data scientist in their corner are the ones who can constantly improve on their product, customer experience, and relations, marketing material, and the efficiency of their stores.
Data science can be a very cool job, believe it or not. For example, you could work with a sports team’s front office and help them with analytics. You could also work with scouts to help delve deeper into their data and come up with new data sets and formulas to calculate and predict performance. You could help a team identify some of their deficiencies so they can improve their strategies.
On the other hand, you could decide to work as a disease mapper. This is the type of job that will grow in popularity in the future, and one that very few will be skilled for. You will be at the forefront of fighting pandemics and coming up with predictive models. You’ll also be able to measure the efficiency of certain procedures.
Other great career options for the future include roboticist, cyber city analyst, and anything dealing with autonomous transportation.
Speaking of the future, it looks very bright for data scientists at the moment. According to the BLS, it is estimated that jobs for data scientists are expected to grow by 15% leading into 2029. This is way higher than the average for all occupations. These professionals are very well paid as well, with the median income at around $122,000 per year.
You have to know that competition is increasing and you’ll also need to learn how to get your resume in front of the right set of eyes. One of the first things you should do is create and build a GitHub profile. This is a great place to showcase your projects, but also to learn from others who are more experienced than you. You’ll also get recognized by key people and have the chance to network.
You also need to constantly keep adding to your resume. However, go one step at a time. You don’t want to mention that you’re an SQL, Python, and machine learning expert if you’re just dabbling. Dedicate yourself to one and build from there.
Another thing you should consider doing is participating in a few contests. This could be another great way to get recognized by movers in the industry and land a great position. Or, you could decide to start a blog and publish articles. This will also show your expertise and allow you to connect with people who may be able to open doors for you.
Before you decide that you’re going to become a data scientist, you have to make sure that you have the skills and aptitudes needed. You also need to make sure that you’re truly passionate about the field, and be prepared for tough work.
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