Bootcamps and learn to code platforms usually push self-taught programmers to study web development. Most new programmers don’t consider a career in data science, even though it is one of the most in-demand skills. Becoming a data scientist is an exciting, rewarding career, so I put together this guide to help you decide if data science is right for you.
What is Data Science
Data science is a field that involves extracting knowledge from unstructured data. As a data scientist, your job is to use massive amounts of data to create value for your company.
Have you ever noticed how Netflix is eerily good at figuring out what you want to watch next? They can predict your preferences because they have teams of highly-paid data scientists that write algorithms to determine what you want to view using the massive amount of data they collect from their 182 million subscribers.
Of course, Netflix isn’t the only company that uses data to deliver a better user experience. Facebooks’ data scientists predict what kind of content you will like, Google’s data scientists predict what search results will best answer your question, and the teams at Amazon use data science to predict what you want to buy.
How Is the Job Market?
Just because the big technology companies are using data science, however, doesn’t mean its the right career path for you. Let’s take a look at the data science job market in the United States.
According to LinkedIn’s 2020 U.S. Emerging Jobs Report, artificial intelligence specialist (data science) jobs grew faster than any other job in the last five years. In that period, they have grown an astonishing 74% a year.
That’s not to say other programming professions aren’t growing fast. The U.S. Bureau of Labor Statistics predicts web development jobs will grow 13 percent from now until 2028. While that is nowhere near the growth of data science jobs, it is still almost triple the predicted 5% projected growth rate for all occupations during that time.
You may be wondering how high data science job growth affects you? Aside from making it easier to get a job because there are more positions available, it also has another benefit: higher salaries. According to Glassdoor, the average salary for a data scientist in the United States is $113,309. Web developers, however, only make $68,524 a year on average.
What Do You Need to Learn?
So what do you need to learn to become a data scientist? You should study one of the programming languages data scientists favor, a variety of tools, math, machine learning, data visualization, and deep learning.
Currently, Python and R are the two most popular programming languages in the data science world. According to the programming language index TIOBE, Python is the most popular choice among data scientists.
Some of the most frequently used tools for data scientists are SaS, Tableau, MATLAB, Apache Hadoop, and TensorFlow, although the tools you will use will depend on where you end up working.
It would be best if you also studied study math, especially statistics.
Finally, you need to know how to use a variety of databases: both relational and nonrelational, as data scientists spend most of their time working with data.
Is It Hard?
Whether or not data science is harder than web development depends on your strengths, especially with math.
Web developers rarely use math. You can go your entire career without doing anything more advanced than basic math. As a data scientist, that is not the case, as they often use math on a day to day basis.
Although you do need to study math, you may be fine, even if it is not your strength. In a thread on Reddit, a data scientist with a political science degree (username Aorihk) explains his thoughts on data science and math,
My job title is “Data Scientist,” but I’m really more of a “data engineer” (app dev, data pipelining, mining, automation, etc.). I’m decent at math but by no means anywhere near being a mathematician. I’m more of a solutions developer. For example, I’m currently building an analytics web app for my client on the Django framework, while also developing data visualizations in tableau, and ad-hoc data analysis products using SQL and Python. What helped me get into this field was learning Python and SQL on my own time.
As a data scientist, you are also more likely to have to learn skills outside of programming. For example, in my discussion with Forrest Hartley, he mentioned he had to study biology and chemistry in his job as a data scientist working with the human genome. As a web developer, you are always doing the same thing: building websites. While you may occasionally have to learn a new framework, your employer would never ask you to study biology.
If you enjoy constantly learning, that will be a positive thing for you. If not, it could be problematic. But the benefit of having to learn so much is you get to be on the very cutting edge of technology.
How to Learn Data Science
There are many different options for learning data science.
If you don’t know how to program in either Python or R, your first step should be to learn one or the other. Don’t know how to program? It is best to start with Python because it is easier for beginners to understand then R.
If you want to learn Python, you can take Moonshot Coding’s intro to Python course, or find thousands of other Python classes on Coding List. More interested in R? Here are some courses you can take to learn R.
If you learn better in person, you may want to attend a bootcamp. Here is Switchup’s 2020 list of the best data science bootcamps.
Data science is the fastest-growing programming field and one of the highest-paid.
For those willing to put in the effort to learn the skills you need to work as a data scientist, you can look forward to an exciting, lucrative career.
You also don’t need to become a professional data scientist to benefit from studying it. Understanding the basics of data science will make you stand out even if you decide to become a web or app developer.
I hope this article helped you decided whether you are interested in a career in data science.
I would love to hear your thoughts on what path you decide to take.
Let me know what you decide in the comments.
If you are working as a data scientist, I would love to hear your thoughts in the comments as well.
Thanks for reading!