Project Manager at computer examining code and working on project

Although data science is still a relatively new career field, roles that require data science expertise are considered to be some of the most exciting and highest-paying jobs in America.

Not only has the profession experienced 650 percent job growth since 2012 (according to LinkedIn), the U.S. Bureau of Labor Statistics estimates that an additional 11.5 million new jobs in the field will be created by 2026.

Despite rising demand, and the fact that more colleges have started to offer formal degree programs in data science and/or data analytics in response to the talent shortage, it’s not entirely clear what education someone needs to break into the field. That’s because data science is a multidisciplinary profession that now encompasses a multitude of positions, and the requirements vary between jobs.

To help clear up the confusion, here’s a look at the best degrees for a career path in data science.

Do you even need a degree?

Technically no, you don’t need a college degree to land a data science job.

First and foremost, what employers are looking for is someone who has the skills and ability to do the work, explained Benjamin Taub, CEO of data science staffing and recruiting firm Dataspace. Hiring managers typically want to see more education or strong field experience, he added.

To qualify for most jobs, you’ll need to understand how databases work as well as the ability to collect, organize, manipulate and analyze structured and unstructured data, draw conclusions, visualize and communicate the results. You’ll also need programming skills and “soft skills” such as problem-solving, continuous learning, passion and the ability to think outside the box. (See a complete list here). A data scientist does their best to predict how data-based strategies will play out over the long term, so intuition is also key.

If you don’t have extensive experience with quantitative or data-related tasks such as data mining, data engineering or statistical/data analysis, it may be difficult to understand basic concepts or master advanced tasks, like developing machine learning models from scratch. Even if you’re determined to learn on your own, signing up for an online course (or several) is never a bad idea.

Plus, data science pros with a bachelor’s degree earn $8,736 more per year than any other bachelor’s degree jobs according to IBM. At that rate, a college degree will pay for itself fairly quickly.

Many organizations also filter resumes by the presence of a college or advanced degree. IBM states that 61 percent of data scientist and advanced analysis positions are available to bachelor’s degree holders, while 39 percent require a master’s degree or a PhD. If you’re shooting for a high-level position like data scientist, consider that you’ll also be competing against other highly educated professionals: according to KDnuggets, 88 percent of data scientists have at least a master’s degree, while 46 percent have PhDs.

But Matt Stabile, COO and data science executive recruiter for recruiting firm Averity, cautions against getting too hung up on “pedigrees” and job titles. For most jobs, a master’s degree is nice to have but not necessarily required.

“Do whatever you can to get your foot in the door and gain experience,” he advised. For most employers, results matter more than college degrees. Once you learn how to gather requirements from stakeholders and generate real-world outcomes, you will be able to compete for many jobs in the field.

Best Degrees

To be clear, finding a curriculum that will prepare you for a specific role or specialty is the best way to maximize the return on a college degree.

Earning a degree in a quantitative field such as finance, economics, mathematics or statistics would also provide you with the fundamental skills needed for a job involving data science, noted Katie Magill, lead technical recruiter for Dataspace.

A STEM degree is likewise a good choice, especially if you want to pursue a career in data engineering, database management and data architecture, or machine learning. A degree in business, accounting or marketing that includes courses in math and statistical analysis can prepare you for a role as a business or market analyst.

Programming skills are also a must-have for every data science professional. At a minimum, you will need to learn how to store, access and manipulate data using Python and popular data analytics tools like SAS, Hadoop, Spark, Hive, Pig and R. Depending on the role, it may help to have a basic understanding of Perl, C/C++, SQL and Java.

To give you the tools necessary to succeed in the workplace, a degree program needs to provide hands-on experience through student projects and internships where you can master the data science process. 

Presenting findings or recommendations requires nuances and knowledge of the audience, Stabile noted. Learning how to tailor your results, what information to include, and how to relate your message to the bigger picture may be the most important data science skill of all.


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