Master’s Degree in Data Science
A master’s degree is the next educational step for students with an existing bachelor’s degree. Earning a graduate degree from a university opens up a new level of job opportunities. Graduates with a master’s degree have access to higher salaries and advanced positions at top companies.
Is a master’s degree in data science worth it? It depends on the field you choose, but for many people, a data science master’s degree is worth it. And though higher education is expensive, the additional salary earned by master’s degree holders can eventually offset the cost. Here’s everything you need to know about data science master’s degree programs.
Overview
A master’s degree is the first graduate degree students earn. After finishing an undergraduate program in a data science field, students can apply to graduate school to continue their education. Students who received a generalized technology degree will pick a specialization during a master’s degree program.
Data science graduate students have many options for numerous degree programs that fall under the ‘data science’ umbrella. Data science students can earn master’s degrees in everything from business administration to software engineering.
Study Data Science is here to provide you with the information you need to know before applying. Here are some essential facts about bachelor’s degrees and college education in general:
What is a Master’s (MS) Degree in Data Science?
A master’s degree in data science can mean many things. Generally speaking, students with a bachelor’s degree (who are seeking more education) can earn a master’s degree from an additional 1.5 to 2 years of education.
A master’s degree demonstrates a high level of competence in a field. Due to the limited availability of dedicated ‘data science’ master’s degrees, students often focus on a related field. Data science graduates often study statistics, computer science, and some level of software development.
A master’s degree program is an opportunity to specialize. The nature of the modern economy rewards highly-trained specialists, so an advanced degree in the field is an excellent opportunity. Financial incentives drive many graduate students, as the average 17% increased earning potential makes a significant difference in the data science field.
MS in Data Science Benefits
The benefits of a master’s degree (MS) in data science are hard to ignore. For one, salaries for MS holders are significantly higher. Also, graduates with advanced degrees are more likely to land better jobs at bigger companies.
Some people claim that a master’s degree is what a bachelor’s degree used to be. Opinions aside, there’s no denying that advanced degrees increase your chances of landing a job. Studies find that the vast majority (72%) of hiring managers believe that master’s degree holders are more qualified for jobs.
Data Science Job Prospects
Job prospects for data scientists are quite good. There’s a labor shortage in the data science field, and the market continues to grow without enough professionals to fill available positions. This trend shows few signs of stopping, so there’s still time to get in while the market is hot. Here are the basic facts about data science jobs.
- Data Science Salary: $118,370
- Data Science Job Growth: 16%
According to the Bureau of Labor Statistics, the market for information science professionals (including data science) will grow an astounding 16% between 2018 and 2028. For reference, the national average growth rate is a mere 5.2%. According to the BLS model, data science and related fields will grow three times faster than the rest of the economy.
In short, computer science is a future-proof career field that’s worth considering. Computer science salaries are high, and opportunities are plentiful. An associate’s in computer science is an excellent way to test the waters and see if an IT career is right for you.
Data Science Certifications
A master’s degree is an excellent way to demonstrate proficiency in a field. Some people substitute higher education for certifications, allowing them to specialize in several fields and expand their employment prospects. However, people who earn a master’s degree and additional certifications have the greatest advantage. Here are some of the most common data science certificate programs:
Data analysis is one of the largest data science specializations. These professionals often earn certifications from the CAP (Certified Analytics Professional) organization to verify their skills. Certification exams from CAP cost $695.
Want to expand your professional expertise and work with popular software systems? Cloudera has the solution with its 120-minute SQL and data analytics certification. The examination costs $295 per attempt. Once passed, the certification is valid for two years.
Shopping giant Amazon offers a specialized big data certification. The examination costs $300 overall and offers numerous advantages to data science professionals. There’s one caveat—you need at least two years of professional experience to earn the certification.
Oracle is a cloud computing and data industry Titan. Oracle systems are common across America. As a result, many data professionals take Oracle’s $245 exam. Once complete, the certificate allows data scientists to work with Oracle systems.
Oracle is another industry giant. Data scientists can familiarize themselves with Oracle cloud computing and data systems for additional opportunities. The exam costs $245 overall, and the certificate stays valid indefinitely.
Data Science Master’s Degree Jobs
Jobs for data scientists with master’s degrees are abundant. A quick glance at any job board reveals a few things: there are tens of thousands of data science jobs available, and many employers prefer experienced/educated professionals. A master’s degree provides a competitive edge and a chance to land senior positions. Here are some of the most common data science jobs:
Data Scientist
General data science positions cover a wide range of job responsibilities. These professionals often spend their time working with analytics tools, databases, and large data sets.
- Salary: $118,370
- Job Growth: 16%
- Total Employment: 31,700
Data Analyst
Data analysts specialize in making sense of large data sets. Businesses hire data analysts to interpret data, identify trends, and conduct market research using data mining.
- Salary: $62,453
- Job Growth: 11%
- Total Employment: 100,000
Machine Learning Engineer
Machine learning is an emerging field with numerous opportunities for data professionals. This artificial intelligence-related specialization is fascinating and lucrative.
- Salary: $114,121
- Job Growth: 344% (growth in the field 2015-2018)
- Total Employment: 10,000+
Database Administrator
Database administrators, managers, and operators with a master’s degree are often the most well-educated (and highest paid) professionals in this specific field.
- Salary: $82,050
- Job Growth: 5%
- Total Employment: 383,900
Graduate School Accreditation
Checking accreditation is essential when choosing a graduate school program. The vast majority of well-known universities are regionally or nationally accredited, though some so-called ‘diploma mills’ tout misleading information about how accreditation works.
Generally speaking, master’s degree students want to attend a school that is regionally accredited (or nationally accredited in some cases). Here are the basic facts about common accreditation types:
National Accreditation
Nationally accredited institutions often focus on specialized subjects such as theology or arts. Many online colleges and specialized degree programs are nationally accredited.
Institutional Accreditation
Institutional accreditation is valid within the institution or system of schools that issue the accreditation. This subtype generally applies to courses and activities hosted by schools.
Specialized Accreditation
Specialized accreditation applies to career-specific programs, and national organizations often issue this form of school certification to professional degree programs.
Regional Accreditation
The majority of universities and graduate schools are regionally accredited by one of seven regional entities. In short, most graduate students should look for this type of accreditation.
Graduate School Admissions
Graduate school admissions are complex and varied, but some general rules apply. The primary factors considered by admissions staff include college GPA, specialized test scores, and even previous work experience. To sum it up, schools require a basic set of performance data. Beyond that, institutions choose whatever factors they want to determine your eligibility. Doing more in college (and doing it better) increases your chances of admission into a graduate degree program.
Bachelor’s Degree (Transcripts)
Students need a bachelor’s degree to complete a master’s degree. After all, that’s why they call it a ‘graduate’ degree. Schools require your degree along with a set of college transcripts. Students with higher GPAs (grade point averages) are at an advantage.
Specialized Test Scores
Some master’s degree programs require specialized testing. Examples of these tests include the MAT, GMAT, GRE, and LSAT exams. Students must also pay for some specialized exams, so remember to factor testing costs into your budget.
Data Science Master’s Degree Cost
Master’s degree programs are expensive. Students justify the cost due to the numerous societal and social benefits of earning an advanced degree. Tuition costs vary widely between schools, and even between programs. And while the average student takes 1.5 to 2 years to complete a master’s degree, the amount of time spent at school has a big effect on how much it costs. Today, the average cost of a master’s degree is $40,000. Students can save money by earning scholarships, finding tuition discounts, and attending a local school to get in-state tuition discounts.
Scholarships for Data Science Master Degrees
There’s plenty of funding opportunities available for college students through scholarships. Scholarships are, in many cases, easy money. Many students don’t even realize that they qualify for free education cash, so be sure to investigate and apply.
Master’s Degree in Data Science Tuition Discounts
Financial aid (in the form of discounted tuition) is available to many data science graduate students. Some tuition discounts may require making hard decisions, like choosing to stay home and attend a local school for in-state tuition.
Student Loans and Financing Rates
Student loans are available for most graduate students, and they’re an option if you can’t pay tuition upfront. Remember, America has an out-of-control student debt crisis, and bankruptcy doesn’t dismiss student loans. Approach lenders with caution and know the facts before signing.
Data Science Master’s Degree Curriculum
A master’s degree program is an opportunity to specialize in a specific field. Data science students often choose to focus their expertise on business, finance, artificial intelligence, and other large ‘niche’ markets. Data scientists come from many degree backgrounds, so here’s a general list of what to expect in graduate school.
Mathematics
Master’s degree students often study mathematics, especially in advanced STEM fields such as computer science. Each school determines what level of proficiency students should receive. Some students finish the most relevant math classes during undergraduate studies.
Coding and Programming
Students sometimes opt to study high-level programming during their master’s degree programs. The most commonly used data science programming languages are Python and R, though students often study additional languages in school, like Objective-C.
Statistics
Data scientists are also skilled statisticians. Many master’s degree students choose to focus on statistics, predictive modeling, and similar courses. Overall, statistics is one of the most beneficial fields of study for master’s degree students.
Thesis and Projects
A master’s thesis is a big part of the degree program. Students choose a specific topic or project to focus on. After, they write a large thesis paper on the topic, usually between 40 to 80 pages long. The thesis is the ‘capstone’ project of a master’s degree course.
Data Science Master’s Degree Courses
Most schools don’t offer a dedicated data science master’s degree program. That may change sometime in the future, but for now, students must choose another program in most cases. The most common are software engineering and computer science. To give you a better idea of what to expect during a data science master’s program, here are some of the top courses taken by data scientists:
Computer Programming
Programming is a popular course choice in the field of data science. Software engineering students spend the most time in these classes.
Analytics
Data analysts and data scientists analyze data and help businesses make use of it. Students who choose to specialize in analytics have many course options.
Databases
Master’s degree programs sometimes offer advanced database courses. These classes offer numerous benefits to data science students.
Applied Predictive Modeling
Predictive modeling is a big part of many data science careers and specializations. Master’s degree programs give students a chance to become experts in the subject.
Statistics
Again, statistics are fundamental to data science. Statistics courses are a great way to prepare for the job during graduate school.
Data Visualization
Data visualization is one of the primary skills used by data analysts to help businesses understand data. Courses in data visualization are common in master’s degree programs.
Online Master’s Degree in Data Science
Online degree programs are less common for master’s degrees, but they’re available in some situations. Generally, master’s degree programs don’t require the same level of rigid 9-to-5 attendance that undergraduates need. Students have more flexibility and independence. For students seeking even more freedom, an online master’s degree is a great choice.
When considering a school, be sure to check accreditation carefully. Also, determine if you want a synchronous or asynchronous schedule. A synchronous schedule requires attendance at predetermined times and often includes live instruction. Meanwhile, asynchronous courses are more flexible; students attend class and complete tasks (mostly) on their own time and when they choose. Here are some of the benefits of online degrees:
Flexible Degrees
Asynchronous courses are flexible and allow students to choose their schedules. Synchronous degree programs also provide some level of flexibility.
Cost Effective Education
Some graduate schools offer online courses at a lower price. This also allows students to save money on transportation, rent, and relocation costs.
High-Quality Education
Online master’s degree programs offer the same high-quality curriculum as in-person colleges. Often, these courses come from the same well-known institutions.
Learn and Work
Students often take advantage of flexible courses to work or take internships. This allows students to pay their way through school and efficiently advance their careers.
Data Science Education Pathways
After completing your bachelor’s and master’s degrees, you can continue college and earn more advanced degrees in the same field. Some students also opt for specialized coding career programs called coding bootcamps, which equip them with the necessary technical skills for the rapidly-evolving world of data science.
Advanced Degrees
Students who complete a master’s degree are eligible to apply for a doctorate program. Post-doctorates are also available, along with additional bachelor and master degrees. Students can (theoretically) earn as many degrees as they want.
- Program Length: 3 – 7 Years
- Average Cost: $48,900 Total
Coding Bootcamp
Coding bootcamps are fast-tracked career training programs with job placement built into the design. These programs omit general education in favor of technical and in-demand skills. Bootcamps commonly offer alternative financing and job placement guarantees.
- Program Length: 3 – 12 Months
- Average Cost: $13,500 Total
Data Science Degree Options
Data science degrees are uncommon. To get a better idea of how to become a data scientist, we can examine the degrees that most data scientists earn instead. Among these are computer science, data administration, software engineering, and business analytics. Here’s more information on these education pathways.
Computer Science Degree
Computer science is a good choice for aspiring data science professionals. A bachelor’s and a master’s degree in computer science will provide an excellent foundation for a data science career, though additional on-the-job or bootcamp training may be advantageous.
Data Administration Degree
Data administration is a growing career path, and many universities offer degree programs in the field. Data administration professionals are well-versed in the intricacies of databases, which is an advantage for students seeking a career in many data science fields.
Software Engineering Degree
Software engineers are (arguably) the strongest programmers in the group. Their skills will help them immensely in a data science career. These students are also exposed to many data science fundamentals during school, giving them an advantage in the field.
Business Analytics Degree
Business analytics is another popular (and profitable) degree path for aspiring data scientists and data analysts. Students in this program learn valuable skills that will help them excel in the workplace. Plus, business analytics jobs pay impressive salaries.
Data Science Professional Organizations
Data science students should consider joining a professional organization. This is especially true during a master’s degree program. Professional organizations provide world-class events and networking opportunities. Sometimes, such activities lead directly to job offers and important connections with industry leaders. Here are some of the top data science professional organizations:
INFORMS, the Institute for Operations Resources and Management Services, is a popular professional organization for information scientists alike. The organization holds annual conferences and offers networking opportunities for data professionals.
The Association for Information Science and Technology, or AIST, is a large computer science organization directed towards data professionals. The group provides jobs, networking opportunities, and information science resources.
The globally-active International Institute for Analytics, or IIA, is a well-renowned organization that serves analytics professionals across the world. The institution offers leadership training, seminars, events, technology resources, and additional member perks.
The Association for Information Systems is a well-known professional organization designed to support information and data scientists. Members of the AIS have access to conferences, online webinars, job resources, and more.