How to become a data scientist when you suck at math (2024)

Being mathematically gifted isn’t a strict prerequisite for being a data scientist. Sure, it helps, but being a data scientist is more than just being good at math and statistics. Being a data scientist means knowing how to solve problems and communicate them in an effective and concise manner. It’s a collection of nuanced skills and, chances are, most data scientists need additional assistance in at least one of these skills. So if math is the skill you’re lacking, don’t give up hope!

Thanks to technology, we have computers that do most of the mathematical heavy lifting for us. Phew! But although we rarely need to do any calculus by hand, we do need to understand why we’re doing what we’re doing. Does the analysis make sense with the data at hand? Is the input data in the right format? What does the output mean conceptually? Have any assumptions been violated in the analysis? Understanding the answers to these questions is much more important than being able to recall the derivative of cosine. That’s what Google’s for.

If at first you don’t understand, try, try again. According to Angela Duckworth’s Grit, passion and perseverance matter much more than innate talent. Everyone eventually comes across a challenge that seems insurmountable. Are you going to let that defeat you? Or will you face your challenges head on? Use the passion that you have for data science to help you cultivate your fortitude and work through the hard stuff!

Telling yourself you’re bad at math is hurting your ability to learn. STOP DOING IT! Instead, visualize yourself as someone who is good at math. Don’t use every mistake you make as evidence that you suck at math. Mistakes are a normal (and necessary!) part of learning and life in general. Plus, working through mistakes will help solidify your knowledge. Expecting math perfection is absurd, so reconcile the fact that someone who is good at math can also make mistakes.

Most people don’t consider themselves to be good at math. So if you’ve managed to understand the mathematical concepts needed for data science in a way that makes sense to you, chances are, you’re going to be better at communicating to a broad audience. People who are naturally good at math often use jargon that they think the general population understands. But if you’re ‘bad at math,’ you know how complicated it sounds and will be able to translate math ‘nonsense’ into perfect sense!