Do You Need a PhD to Become a Data Scientist?
If you are intrigued by a career in data science, you may have been drawn in by its widely reported employment boom. Indeed, the numbers are enticing by any measure: according to the Bureau of Labor Statistics, the average median income for data scientists in 2021 was an impressive $100,910 per year, while the projected job employment growth rate for data scientists is a stunning 36% by 2031. These are numbers that should intrigue anyone with an aptitude for computer science or engineering.
However, despite the exceptional job statistics for data scientists, many are intimidated by the seemingly extensive schooling needed to work as a data scientist earning at that salary level. It’s true that the more advanced a degree one has, the more in-demand they will be for employers, especially for positions at the highest levels of data management and consulting. Some people assume that without a PHD in data science, there will not be the same number of excellent opportunities that are so widely publicized.
So do you need a PhD to become a data scientist, taking advantage of this booming industry? In short, no!
Those who hold master’s degrees in data science are also in competitive positions for top-paying jobs in the field. The truth is, data science is a field in which what matters most is what you actually know how to do – in other words, employers will be concerned with academic credentials insofar as they demonstrate that you have acquired the requisite knowledge to serve as an expert on their team. (Technically, one doesn’t need a degree at all to become a data scientist, although it is by no means easier to receive the necessary education independently, and it is much harder to prove your abilities without a degree.) Since a PhD asserts the highest level of training and education, those who hold them are in the very highest demand for top data science jobs. However, you can certainly become a data scientist without a PhD, and a master’s degree should also take you quite far, asserting a very high level of competence and ability.
This article will discuss different degree and certification opportunities for aspiring data scientists to help you find the path that will meet your existing level of education and areas of interest. To learn more about the educational options that are out there, read on.
If you are interested in pursuing a data science PhD, there are numerous excellent programs that will help you gain the top-level expertise you are seeking. For more information about data science PhDs, with information about available programs, academic requirements, and more, take a look at our guide here.
Bachelor’s in Data Science
If you do not currently hold a bachelor’s degree and feel drawn to the field of data science, getting your bachelor’s in data science can be an excellent way to get your grounding in key concepts in the field. You’ll receive your introduction to the interdisciplinary approach of data science, learn coding languages that are foundational to any data science profession, and explore key issues in the ever-evolving world of big data.
To be clear, a bachelor’s in data science is not a prerequisite to attend a master’s program. (Those who are considering a master’s in data science should take note.) However, starting your education at the bachelor’s level will allow you to start building your competence and insight into the field early, opening up new dimensions of the subject and making you an especially qualified and capable data scientist in the future. You may even be able to find internships or entry-level employment opportunities that will give you your first work experience in the field before you’ve even received your degree. If you’re impatient to break into the arena of big data, finding a bachelor’s program with a major or concentration in data science is the perfect way to hit the ground running.
Top jobs for those who hold a bachelor’s in data science
While a master’s degree in data science will open up top-ranking job opportunities in the field, there are numerous jobs that can give those who hold bachelor’s degrees in data science a leg up in their career. These include the following:
- Database administrator
- Junior data analyst
- Junior data engineer
- Market research analyst
These entry-level roles can offer an on-the-ground education for aspiring data scientists, helping them figure out an area of specialty and build the skills that will allow them to thrive in a master’s program.
To learn more about Bachelor’s in Data Science programs, with information about academic requirements, tuition, community college options, and more, take a look at our guide here.
Master’s in Data Science
When people discuss the many lucrative opportunities that are proliferating in the field of data science, they are most often describing the professional landscape for those who hold master’s degrees. Indeed, a master’s in data science is likely to give you the skills and experience employers are looking for to carry out large-scale operations related to data. If you’re looking to truly take advantage of the tremendous opportunities currently available to data scientists, aiming to eventually receive your master’s degree in data science is the most reliable path to a high-earning career.
Requirements for a data science master’s degree
One does not need to hold a bachelor’s degree in data science in order to apply for a master’s program. Those who pursue advanced degrees in data science typically have majored in mathematics, statistics, or computer science in undergraduate college, though it is possible to enter a master’s program with a prior degree in a totally unrelated field, such as history or political science. No matter what type of bachelor’s degree you hold, there’s no reason to think it won’t be possible to become a data scientist.
What’s most important for prospective data science master’s students to know is that you will be expected to enter with a prior understanding of the fundamentals of programming (including knowing at least one programming language, such as Python or Java), data analysis, statistics, and single-variable calculus. There are many ways to build up the knowledge to get yourself up to speed before starting a master’s program, including summer courses and bootcamps (more information on those later).
Some master’s programs even include preliminary course work for those who are not yet acclimated to the baseline competencies expected of data science students. These can be a great resource for students whose academic backgrounds did not emphasize data science, statistics, or computer science. However, be ready for a great deal of work, as there will be a point in your master’s program where you will be expected to perform the same operations as classmates who arrived already versed in the materials.
Specializations
Since the field of data science is so vast, many decide to focus their master’s degree work on a particular area of specialty, which is likely to help you define a particular career path and enter at a high level. It can be helpful to have this area of expertise in mind before applying to a program, as some schools offer more targeted course work than others.
Some of the most popular specializations within the field of data science include the following:
- Business intelligence (B.I.)
- Cloud computing
- Data analytics
- Data engineering
- Data visualization
- Machine learning (M.L.)
These are just a few of the top focus areas within the field of data science. For more complete information on each topic, visit our guide to data science focus areas here.
Top jobs for those who hold a master’s in data science
Some of the roles available to master’s degree holders are advisory positions who can have a great deal of influence in company decisions, translating key data findings to team leaders that will inform major actions. In short, these are jobs that will require a great deal of expertise, as they will ask you to take a great deal of responsibility.
Some of the top positions for those who hold master’s degrees in data science include the following:
- Business intelligence (BI) analyst
- Data visualization analyst
- Database architect
- Financial manager
- Machine learning (ML) engineer
- Market research analyst
- Senior data engineer
These are just a few of the high-ranking job titles in the world of big data. Many of these correspond with one’s chosen area of specialty in their degree program. It is also worth noting that some who hold these positions work their way up from lower-ranking roles on their team, building their expertise and proving their competence until they become the trusted authority on staff for matters related to data, analytics, and programming.
For more information about master’s in data science programs, including standard course offerings, part-time options, and details on specific programs in your area, take a look at our complete guide here.
Associate Degree in Data Science
If you do not hold any higher education degree and would like to take your first steps in the field right away, it is possible to get your associate’s degree in data science, which will help you build the foundation from which you can pursue a career in big data. It is important to note that these programs alone are not likely to make you a candidate for the high-level data science jobs that draw many to the field, but they will give you a baseline knowledge in the discipline as a whole and typically will give you transferable course credits if you choose to pursue a bachelor’s degree.
Topics in associate’s degree programs tend to include introduction to programming, database statistics, software design, calculus, business fundamentals, and more. These units will be a great opportunity to help you get a grasp on the variety of job opportunities in the world of big data and could lead you to determine your area of focus when pursuing a bachelor’s or master’s degree.
For a complete guide to associate degree programs in data science, take a look at our guide here.
Data Science Certificate Program
If you are looking to build proficiency in some of the fundamental skills needed to become a data scientist but don’t have the time to take on a full-blown degree program, there are many certification programs that can provide a basic orientation for you in the field of big data. These programs are also excellent options for those who do hold advanced degrees but would like to advance a particular area of focus that they may not have studied while in school.
Typically, certificate programs are far less intensive than degree programs, making them advantageous for those who have too many other responsibilities to enroll in graduate school. They also tend to be more affordable than more rigorous degree programs.
Certificate programs in data science can be a great option for dedicated individuals who have a very focused agenda for pursuing further knowledge of the field in the first place. However, it is important to keep in mind that simply holding a certification in data science is unlikely to give you the qualifications needed for the top-paying jobs in big data, which tend to call for the level of expertise imparted by a master’s or PhD program.
To learn more about data science certificate programs including career building opportunities, admission requirements, and more, visit our comprehensive guide here.
Data Science Bootcamps
If there is a particular skill set you are hoping to develop or an entry-level, project based position you are hoping to find in the world of big data, then a bootcamp could be a great option for you. There are bootcamp offerings in a wide variety of subjects and some are designed to set you up with your first work experience in a data science related position. As with certificate programs, it’s important to know that these bootcamps will not alone give you the expertise needed to launch a career working in big data at the managerial or executive level, but they can be a path to your first work opportunities in the field, helping you cultivate a particular ability in coding or data engineering in a minimum of time.
Boot camps tend to be time-intensive but short, held in courses that typically last from eight to 15 weeks. Many of these programs have turned to online options so that students can attend from all over, but it’s important to set aside the proper amount of time to do the work they require – despite their convenience, boot camps aren’t easy, and in order to get the most out of their course offerings, you’ll be expected to put in the time. For this reason, some people find that in-person bootcamps are a more productive use of your time, and given that there are still so many courses out there, you are more than likely to find an in-person course in your area.
If you’d like to know more about data science bootcamp options, survey the course offerings that are out there, and find out if this path is the right one for you, visit our complete guide here.
