What Does a Data Science Major Do?

What You Study in a Data Science Degree Program

Data science degree programs cover various topics to teach the foundations of data science and help students hone their data science skills. Common topics covered include:

• algorithms
• artificial intelligence and machine learning
• computational structures
• data analytics
• data mining
• data structures
• database management
• statistical analysis

Data science programs are often heavy in math, with courses in calculus and linear algebra. You may also be required to learn programming languages like Python.

Specializations in Data Science Degrees

Data science degree programs may offer specializations or concentrations that allow students to tailor their courses to a specific career goal. Specializations in data science may include:

• biology and medicine
• computational and inferential depth
• cybersecurity
• human context and ethics
• mathematics and computation
• modeling, learning, and decision-making
• probability

What Can You Do With a Data Science Major?

A degree in data science can prepare students for high-demand careers in data science. Below, we've listed some common careers for data science majors.

Data Scientist

Data scientists collect, analyze, and determine how to use data. Their jobs may include:

• determining what data is needed for a project
• gathering data
• analyzing collected data
• present findings to businesses
• make recommendations based on data analysis
• create, test, and update data algorithms and models

Typically, data scientists work in an office setting, although they may work in many different sectors. According to the U.S. Bureau of Labor Statistics (BLS), demand for data scientists is projected to grow 35% by 2032, much faster than average.

Data Analyst

A job as a data analyst is a great entry-level role for those wanting careers in data science, but can also be an excellent long-term career as well. Data analysts collect, process, and analyze statistical data to help companies make business decisions.

Like many other data science jobs, data analysts work in offices and may work with others like business analysts and data scientists.

Database Engineer

Database engineers are responsible for designing, building, and maintaining a company's information technology or big data infrastructure. Their jobs often include:

• developing and designing infrastructure and interfaces so businesses can collect and store data
• building data pipelines to process data
• creating an interconnected data ecosystem that makes data accessible to the data scientists
• testing and maintaining these systems

This role is slightly different than that of other data science professionals as it focuses more on the hardware and software that processes data, rather than the actual data. Database engineers often need several years of experience and must know multiple programming languages.

Statistician

Statisticians use mathematics to analyze data and figure out how to use this data to solve real-world problems. They can work within several fields, including:

• academia
• government
• healthcare
• research and development

Statisticians usually work in an office setting and are often part of a team of specialists like engineers or chemists. According to the BLS, jobs for statisticians are expected to increase by 32% over the next decade.

Machine Learning Engineer

Machine learning engineers are focused on analyzing big data using AI and machine learning. Their job may include:

• designing and building machine learning systems
• testing these systems
• creating data funnels for big data
• monitor the machine learning systems to ensure accuracy

This career usually requires several years of data science experience as well as knowledge of multiple programming languages. Machine learning engineers are in high demand across multiple business sectors.

Applications Architects

Applications architects are responsible for designing the overall framework of software applications. Their typical tasks often include:

• tracking applications used within a business
• interpreting how the applications interact with each other and with users
• designing applications
• building application components like user interface and infrastructure

Application architects need to know programming languages as well as the needs of a business. This is one of the higher-paying roles in data science and often requires only a bachelor's degree.

How To Pursue a Degree in Data Science

To pursue a degree in data science, you'll first want to find a school with a strong data science program. Then you'll apply and wait to find out if you've been admitted.

Some colleges and universities will have you declare your major right away, while others will have you wait until your general education courses are completed. If your college has you wait, speak with your admissions counselor about the best general education courses for a data science major.

If you're still in high school, it helps to ensure that your curriculum is strong in science and math. Many colleges and universities will post their high school course expectations on their websites.

FAQs About Data Science Majors

Below, we've answered some frequently asked questions about data science majors.

Is Data Science a Hard Major?

Data science is a major that can be hard for some students. It requires a lot of math and science courses, which can be difficult. However, students who enjoy these subjects may have an easier time with this major. Overall, it depends on what your strengths are.

Should I Get a Master's Degree in Data Science?

Whether or not you should get a master's degree in data science depends on your career goals. Some data science career paths are more likely to require master's degrees for entry, such as:

• data architect
• statistician
• machine learning scientist

What Skills Are Essential for a Career in Data Science?

A data science career often requires a skill set that includes:

• analytical skills
• computer skills
• logical thinking
• math
• problem-solving