“Should I pursue a career in data science?” This is one of the most common questions I get asked these days.
There are several obvious reasons why someone might want to become a data scientist. It’s a high-paying job, it’s in demand, it’s high-tech, and it’s rather prestigious within the tech industry. While all of these might sound like great reasons to become a data scientist, they really say nothing about whether you’ll actually enjoy your day-to-day job in data science.
So, to help those of you who are struggling to decide whether this career path is right for you, I’d like to offer you some advice from my own experience. Below are the top six traits I see in people that enjoy doing data science for a living.
Data scientists are very curious by nature. We have a desire to understand how the world works and use this knowledge to our advantage. This desire to understand our world compels us to invest time and effort in collecting, organizing, and analyzing data. If you’re not a naturally curious person, you likely won’t enjoy spending countless hours analyzing data to learn the answer to some random question.
Data scientists are generally distrustful of information that is not backed up by empirical evidence. The more incompatible this new information is with our existing beliefs about the world, the more evidence we’ll require to change our beliefs. Skepticism is necessary for science. However, the mark of a good scientist is that we keep an open mind and update our beliefs when presented with new evidence.
Data science is built on a foundation of math and statistics. You don’t need a Ph.D. in math or statistics in order to be a successful data scientist. However, you do need to be comfortable with math and statistics so that you can understand the tools you’re using. More importantly, this will help you avoid making mistakes due to a lack of understanding of the limitations of your tools.
As a data scientist, you will likely spend roughly 80% of your time writing code to transform and clean data in order to prepare it for analysis or to build a model. For the “sexiest job of the 21st century“, the sad reality is that we spend most of the time as “data janitors“. So, you need to enjoy writing code and working with data in order to enjoy working as a data scientist since that’s what you’ll likely be doing most days.
A large part of data science is learning how to deal with uncertainty. Some people handle uncertainty very well, while others really struggle. When I’m programming, there’s very little uncertainty — the code will do exactly what I tell it every time it runs, with few exceptions. However, when I’m analyzing data, no matter how confident I am in my data, analysis, or assumptions, there will always be some degree of uncertainty.
The field of data science is changing rapidly. We have new tools, frameworks, and methods emerging on a daily basis. In fact, it’s probably one of the fastest-evolving tech fields today. In order to keep up, you’re going to have to be continuously learning new skills. So, if you love learning, this is a great field to be in. However, if you dislike learning, you’ll likely struggle to keep up for the rest of your career.
While there are definitely other key attributes that I see in people who enjoy their careers in data science, these six stand out the most to me. In addition, I think these attributes are good predictors of whether someone will enjoy doing data science for a living. I hope this information helps you to decide if a career in data science is right for you.
Also, please keep in mind that you don’t have to become a data scientist to work in the data science field. If investing the time to become a data scientist isn’t right for you, there are still several other job roles that exist in this space. For example, you could become a data analyst, data engineer, machine learning expert, or domain expert.
If you’d like to learn more about a career in data science, please check out my courses on data science.