Data scientists are able to convert numbers into actionable business goals, help companies make smarter decisions, and even predict the future through machine learning and artificial intelligence. With all that influence, it’s pretty clear why it’s become one of the most competitive career tracks in tech.

And as you know, there’s a hefty amount of math involved. But you may not have to master linear algebra, advanced calculus, and probability theory. You can narrow down your must-have math skills based on your specific career goals.

We asked some of our data science mentors, students and course designers about the math involved in the field, and in our course. Here’s their take on which skills are most important.

What types of math are used most often in data science?

Statistics is used in every level of data science. “Data scientists live in the world of probability, so understanding concepts like sampling and distribution functions is important,” says George Mount, the instructional designer of our data science course.

But the math may get more complex, depending on your specific career goals. Some popular specializations within data science, like machine learning, require an understanding of linear algebra and calculus.

How much math will I be doing in Thinkful’s course?

In our course, you’ll learn theories, concepts, and basic syntax used in statistics, but you won’t be required to do much math beyond that. George explains, “we emphasise practice over theory. So while students will learn some of the hard math behind the algorithms, the emphasis is on understanding how to use them effectively in a business context.”

Students who are interested in specialties like machine learning may choose to study calculus and linear algebra more deeply. Even though those math skills aren’t required to complete the course, you can apply them in your capstone project, and also work with your mentor to better understand the more advanced math.

Thinkful mentor Abdullah Karasan, who has a PhD in financial mathematics, notes that “considering the Thinkful bootcamp is machine learning intensive, linear algebra and optimization knowledge can help students digest the concepts.” So if you’re up for the challenge and it serves your career goals, delve deeper into the math while you have an experienced mentor at your side.

Which has more math: Data Science Immersion or Data Science Flex?

Data Science Immersion and Flex both cover the same content and curriculum. So if you’re undecided between the two, choose the one that fits your schedule. Here’s a breakdown of the differences between our course formats.

Should I brush up on my math skills before applying?

You won’t have to pass a test or demonstrate any specific math knowledge to qualify for the course.

That said, it wouldn’t hurt to have a general understanding of statistics. If you refresh your stats knowledge before the course begins, the material will come more easily and you’ll be able to focus your mental energy on other areas of the curriculum (like learning SQL and Python, for instance).

Matt Shull, who helped create the Data Science Immersion program, sums it up: “basics of statistics is a huge plus. If you don't have that knowledge but you're comfortable with numbers and did well in college level math courses, then you'll likely do very well.”

Consider your career goals.

Keep in mind that some data science jobs are more math-heavy than others. If the thought of derivatives and logarithms sends chills down your spine, you might have an extra challenge pursuing AI or machine learning. Research the areas that interest you to get a clear understanding of the skills needed down the road.

If you want to leverage your existing expertise from other areas, our data science course could prepare you for job titles you haven’t yet considered. Thompson Liu completed Thinkful’s data science program and went on to become a Financial Analyst for Texas Instruments: “I would argue that the Data Science course is a great tool to use if you are trying to be a Corporate Financial Analyst since it allows you to triangulate forecasts for net revenue.”

When in doubt, ask.

We work with prospective students one-on-one to make sure you’re a good fit for the course. If you have any questions about the course material or requirements, we’ll give you all the information you need before you commit.

Interested in flexing your math muscles with a data science career? Let’s chat about how Thinkful can help you reach your goals.  

Share this article