The world is awash in data, and companies in every single industry—from retail and health care to manufacturing and finance and beyond—are looking to harness that information to elevate customer experiences, deliver relevant products, increase efficiency and improve their overall business decision-making.
The U.S. Bureau of Labor Statistics projects this interest in big data will help grow mathematical science occupations 27.9 percent from 2016 to 2026, much faster than the average for all occupations, resulting in 50,400 new jobs. Combined with this demand is a shortage of qualified data scientists, which means higher salaries and other perks.
Glassdoor has named data scientist the No. 3 best job in America for 2020 after taking the top spot from 2016 to 2019. Data scientists enjoy a median base salary of $107,801 per year and rate their job satisfaction at 4.0 on a scale of 1 to 5.
So what exactly is data science and how does it fit into your education and career?
Data science is about all the new information that has only recently become available, largely due to advances in technology, and cannot be processed using traditional techniques. Some of it is “big” and so requires new tools.
Examples include location-tracking technology in phones and other smart devices, which can provide insight into the movements of large groups of people. Other examples are remotely sensed images that when paired with machine learning can give detailed information about natural resources, our environment and infrastructure.
Data science, then, means using statistics and computer science, among other skills, to collect, clean, organize, store and analyze that information in order to make evidence-based business decisions.
If you’ve got an undergraduate degree in computer science, math, physics or another related STEM field, you’re already well prepared to become a data scientist. Even better if you already have industry experience and ideas for what you’d like to achieve using data science.
A master’s degree in data science will give you all the skills and knowledge you need to become a data scientist in any industry—a strong foundation in both statistical methods and computing techniques. Graduate certificate programs will focus on certain facets of the discipline, or how data science is applied to specific fields or industries, but they can also count toward an advanced degree if taken at an accredited institution.
At Colorado School of Mines, for example, the non-thesis master’s program is built on three modules, each consisting of three 3-credit courses: data modeling and statistical learning; machine learning, data processing and algorithms and parallel computation; and domain-specific coursework. The program also includes a mini-module with 1-credit courses in research ethics, leadership and teamwork, and professional oral communication.
For those looking to add data science to their skill set without a master’s, Mines offers certificates that focus on the foundations of data science, statistical learning, computer science and applying data science to business, the petroleum industry and earth resources.
The first step is deciding on what you want to focus on. Do you want a full-time position as a data scientist—one who can work on any industry? Are you looking to incorporate data science principles to advance in your current position in a particular industry?
Once you’ve decided to make the data science leap, it’s time to turn yourself into the ideal advanced degree program candidate.
Looking for more examples of how data science can make an impact on your career and your industry?