Data Science Degrees

Updated December 22, 2022

Data science degrees are growing in popularity, and for good reason. Explore degree options and why the field of data science may be the right career path for you. is an advertising-supported site. Featured or trusted partner programs and all school search, finder, or match results are for schools that compensate us. This compensation does not influence our school rankings, resource guides, or other editorially-independent information published on this site.

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What Is Data Science?

Data science explores data for use in problem-solving and decision-making tasks. Pioneered by educator and statistician John Tukey in the 1960s, data science uses computational data to provide solutions in various applications. Today, business owners rely on professionals with data science degrees to solve financial and operational problems for companies.

A computer science concentration, data science differs from other specializations in its emphasis on mathematical use of technology. While computer science generally focuses on computers and how they operate, data science uses computers to generate and analyze data with mathematical models.

Multiple industries employ data scientists, including finance, healthcare, manufacturing, and retail. Most entry-level data science positions require a bachelor's degree, and learners may pursue a master's degree for more advanced roles and higher salaries.

Data science and similar mathematical occupations employ an estimated 59,680 professionals with a median income of $98,230, according to May 2020 data from the Bureau of Labor Statistics (BLS).

As a whole, technology careers exhibit some of the fastest growth and best salaries. CompTIA data shows more than half of states report almost 8% of their workforce in tech. Data science and similar mathematical occupations employ an estimated 59,680 professionals with a median income of $98,230, according to May 2020 data from the Bureau of Labor Statistics (BLS).

Information security analyst and computer and information research scientist roles are among the fastest-growing data science careers. The BLS projects 31% and 15% growth rates, respectively, for these data science careers from 2019-2029.

Why Get a Degree in Data Science?

Earning a data science degree opens doors to many careers in the computer technology industry. This in-demand specialization leads to high-paying jobs on the cutting edge of technology with room for advancement. Data science degree-seekers learn real-world skills that apply to many jobs and personal computing tasks.

Pursuing a degree in this field presents challenges and rewards. The following list includes a few benefits of graduating with a data science degree.

  • Versatile Employability: Graduates enjoy several career options beyond data science. Professionals may work in technical careers such as database creation or security, and in industries such as construction or healthcare.
  • Fast Growth: According to the BLS, some of the fastest-growing career projections from 2019-2029 include data science roles. Data scientists, statisticians, and information security analysts are among the fastest-growing jobs.
  • Prestige: Data scientists play pivotal roles in business operations as they assist companies with growth and efficiency. Decision-makers look to data scientists for informed suggestions based on their analyses, making them prestigious and respected professionals.
  • Technological Advancement: Learners gain the latest technical skills to provide fresh knowledge to their industry. A master's degree or Ph.D. in data science can offer continuing education to advance professional skills and stay current with new technology and industry practices.

Top Data Science Programs

Explore data science programs to take your career to the next level.

When Is a Data Science Focus Better Than a General Computer Science Degree?

Computer science and data science degrees overlap with program content. Both degrees involve programming coursework, for example.

Data science programs teach specialized skills such as big data analytics, reinforcement learning, data mining, and mathematical modeling. Coursework in data science typically places a heavier emphasis on statistical methodology and theory, including probabilistic systems analysis and probability theory.

Data science programs teach specialized skills such as big data analytics, reinforcement learning, data mining, and mathematical modeling.

Students aspiring to careers in business consultancy, database management, machine learning, and data analysis typically hold a degree in data science.

Graduates in both disciplines enjoy high earning potential and bright prospects in hiring.

When Might a General Computer Science Degree Be Better Than Data Science?

Computer science coursework often emphasizes cybersecurity, algorithms, operating systems, and software engineering. Those with interests in computational design, programming theory, database systems, and architecture may find a computer science degree more suitable.

Students uncertain about their future educational and career path may find that a computer science degree provides greater versatility. A strong foundation for future education programs, a bachelor's in computer science can lead to a master's in data science, should a student later decide to specialize.

What About Other Computer Science Specializations?

Computer science programs offer several specializations in addition to data science that may be more suitable for some career paths. Each concentration provides learners with fundamental coursework for targeted career outcomes.

For example, a computer engineering specialization can lead to computer programming, software development, or computer hardware engineering careers. Web developers and web designers might pursue a web development concentration.

Learn more about select computer science specializations by following the links below.

Types of Data Science Degrees

Students can pursue data science degrees in multiple educational levels, including an associate degree and a Ph.D. Because of the competitive nature of the industry, advanced degrees can set professionals apart in their career search. Master's and Ph.D. in data science programs may also lead to higher salary potential and more available job opportunities.

Below are the most common data science degree levels and important points to consider as you plan your education.

Bachelor's Degree in Data Science

Entry-level data science jobs typically require at least a bachelor's degree. These programs include about 120 credits and take an average of four years to complete, or two additional years after an associate degree. Graduates interested in gaining on-the-job experience or later pursuing a master's degree for career advancement should start with a bachelor's degree.

Master's Degree in Data Science

Most high-level careers in data science, including computer and information research science and data architecture, require a master's degree. Degree-seekers explore cutting-edge technologies and advanced skills such as problem-solving with machine learning and programming languages. Learners should budget 1-2 years, or about 36 credits, to complete a master's degree in data science.

Ph.D. in Data Science

Although data science careers don't often require a Ph.D., the credential may benefit professionals seeking career or salary advancement. This degree leads to roles in research, education, and high-level data management. On average, a Ph.D. in data science takes 3-5 years to complete, including coursework, internships, and dissertations.

Data Science Career and Salary Outlook

A concentration in data science blends essential computer science topics with analytics, mathematics, and information technology studies. Therefore, data science degrees lead to analytical and mathematical computer careers such as computer network architect and computer systems analyst. Because they study computer science subjects like programming languages, algebra, and statistics, data scientists may also land roles as computer programmers and hardware engineers.

Many data science jobs exhibit fast growth rate projections and high median salaries. The BLS projects 15% and 10% growth rates for computer information researchers and database administrators, respectively, from 2019-2029. The BLS data also notes a median annual salary of more than $90,000 for several data science careers, such as those detailed below.

To enter the data science field, learners may begin with a bachelor's degree. Degree-holders can pursue higher-level data science degrees to climb the ladder to more advanced positions with higher salaries. The following list explores a few leading careers in data science.

  • Data Scientist: Data scientists collect and analyze data to find room for improvement. Typically, these professionals work for companies to make finances, workflows, and other business aspects more effective based on computational data. Master's degrees in data science may lead to advanced roles, such as principal data scientist or computer research scientist.
  • Database Administrator: Database administrators create and manage company databases. Their primary responsibility is to design a functional database specific to the company, but they also troubleshoot, update, and secure databases. Entry-level roles require a bachelor's degree, but large companies often seek candidates with advanced data science degrees.
  • Computer Network Architect: Computer network architects design, upgrade, and secure networks for companies. Their primary responsibilities include hardware and software upgrades, network planning, and technology research. Because they need to understand typical business processes, computer network architects often pursue a master of business administration (MBA) after graduating with a bachelor's degree in data science.
    • Required Education: Bachelor's degree; MBA sometimes preferred
    • Job Outlook (2019-29): +5%
    • Median Annual Salary: $116,780
  • Computer Information Researcher: These professionals research and study problems and challenges with computer systems. Computer information researchers may work for technology companies to develop new systems or upgrade existing systems. They also assist companies with creating and optimizing in-house computer systems. Most employers require computer experts with an advanced data science degree and training in programming, mathematics, and computer analysis.
  • Computer Systems Analyst: Computer systems analysts suggest and implement hardware and software solutions to businesses. These analysts ensure that decision-makers and users understand how and why to use the new technologies. Entry-level roles require a bachelor's degree, but large companies may prefer MBA-holders for their additional business knowledge.

Additional Resources for Data Science Students

Accreditation for Data Science Schools and Programs

Accredited schools and programs adhere to high-quality educational standards set by accrediting bodies. Regional accrediting bodies endorse schools within a specified United States region. The Higher Learning Commission, for example, accredits schools in Iowa, West Virginia, and surrounding states.

National accreditation generally endorses industry, vocational, and religion-based programs. Most schools and employers value regional accreditation, which signals a school's commitment to education and best practices.

A national accrediting body for data science degrees, ABET endorses engineering, computing, and other technology-focused programs. The Council for Higher Education Accreditation hosts an online database to search for regionally and nationally accredited institutions and programs.

Accreditation benefits schools and learners. Graduates of accredited data science programs typically gain access to more available job opportunities and can transfer their credits more readily to other accredited schools. Additionally, pursuing a degree from an accredited school is a prerequisite for federal financial aid programs.

Paying for Degrees in Data Science

Although investing in higher education can secure a career path for the future, students also incur significant expenses. In many cases, financial aid can assist students with tuition, books, and other costs. Some options for data science degree-seekers include scholarships, grants, and loans.

Follow the link below to learn more about different types of financial aid.

Professional Organizations for Data Science

Professional organizations provide industry-specific resources, events, and opportunities. Members can participate in these organizations to continue their education, network with other professionals and industry leaders, earn credentials, and stay current with data science news. Further benefits include mentoring, workshops and seminars, career development, and members-only job opportunities.

The following organizations assist data science professionals in developing and advancing their careers.

ADaSci brings data scientists together for networking and learning opportunities. The organization also administers the chartered data scientist (CDS) credential through a self-study program. Members receive a CDS exam discount, free industry publications, and exclusive job opportunities.

DASCA develops knowledgeable data science professionals prepared to enter cutting-edge roles. Schools may seek DASCA accreditation for their relevant programs. Professionals interested in leadership opportunities can earn senior or principal data scientist designations through DASCA programs.

DAA enhances research, standards, and advocacy for web and digital analytics careers. Members can pursue a DAA web analyst certification, search exclusive job postings, and participate in events throughout the year. Degree-seekers at member universities can access DAA professional development and networking opportunities through their schools.

Since 1839, ASA has worked to promote and excel statistics and data science professions through law, education, and the help of industry leaders. Individuals and organizations can become members to receive discounts, ASA publication access, and career development opportunities.

Frequently Asked Questions About Degrees in Data Science

How long will it take to complete a data science degree?

The length of data science degrees depends on the degree level. Typically, an associate degree takes two years, a bachelor's degree takes four years, and a master's degree takes two years. A Ph.D. program typically takes 3-5 years.

What salary will a data science job pay?

The average data science job salary reaches $80,000+, although specific salaries vary depending on location, job title, and career level. On the higher end of the spectrum are roles requiring specialized knowledge and higher degree levels, like computer information researcher and computer network architect.

What job can I get with a degree in data science?

Degrees in data science lead to high-paying careers like database administrator and computer network architect. Data science graduates may also pursue entry-level computer science roles as computer programmers or software developers.

Are data scientists in demand?

The BLS projects faster-than-average growth in several data science-related careers. For example, BLS data projects a 15% growth rate for computer information researchers and 7% growth rate for computer systems analysts from 2019-2029.

Featured Image: Tom Werner / DigitalVision / Getty Images

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