What skills are needed to succeed in data science?

The world of tech is laser focused on harnessing, organizing, and analyzing data. That should be music to the ears for those with the expert know-how in the industry. But it should also be considered good news for those not as adept with data management since data science jobs are growing fast—and with greater salaries.

In fact, data science and database management skills are one of the top skills managers are increasing salaries for, according to Robert Half’s 2024 Tech Salaries and Hiring Trends guide.

Data science itself is a term used across-the-board to connect areas of AI, machine learning, and statistics and can lead to careers as data scientists, analysts, engineers, and beyond. Many people in the profession consider data skills as paramount to the future.

While not everyone necessarily needs to become a data scientist, everyone needs to be knowledgeable of its data and its pitfalls, says Jignesh Patel, professor in the computer science department at Carnegie Mellon University and co-founder of DataChat—a generative AI platform.

“The study of data science is important because it imparts a systematic way to discover facts and identify falsehoods in a digitized society. Collectively, we are becoming more data-driven, not just in businesses, but in our day-to-day lives,” Patel tells Fortune. 

So, for both sides of the coin—those who are and are not interested in pursuing a career in data science—what are the top skills in the data science field? 

What skills do you need to succeed in data science?

To be successful in data science, you must have a strong knowledge of math and computer science—in addition to soft skills centered around working constructively as part of a team. 

More specifically, data scientists’ core must center around algorithms, code patterns, and interactions between code modules, Patel says.

“The foundational hard skill for a data scientist is statistics. How we…