Compare online data science master's degree programs

Admission requirements for a Master of Data Science online degree

Admission requirements for online data science master's degrees vary by university, but most will require a completed bachelor’s degree from an accredited institution in fields such as data science, data analytics, computer science, engineering or mathematics. Other common requirements typically include:

• Official transcripts

• Résumé

• Personal statement

• Letters of recommendation

• Demonstration of industry experience

• GRE scores

Note that some master’s in data science online programs may not require GRE scores to apply, so make sure to check your preferred program’s requirements. It also may be important to note any prerequisite courses on topics such as programming, statistics, or math.

Master’s in data science online curriculum

An online curriculum in data science will be similar — and just as challenging — as a traditional, on-campus curriculum. Coursework will include topics such as programming, data mining, machine learning, database management and data visualization, and will typically include a mix of core courses and electives. Some online master’s degree in data science programs may offer areas of concentration — like language analytics or data platforms — for even greater focus, and certificate options also may be available.

You can expect to participate in classroom discussions, projects, presentations, and breakout groups, just as you would in a traditional program. You also will have access to your instructors in scheduled office hour sessions, as well as opportunities to connect and ask questions as needed. Additionally, many data science programs include an on-campus immersive experience, during which you will visit, in-person, your university’s campus, for a few days of invaluable networking opportunities, engaging group projects, and meaningful real-world problem solving.

One of the most prominent advantages of a master’s in data science online program is flexibility: Students typically complete coursework on their own schedule and earn their degree while continuing to work in their current career and maintaining their personal and/or family responsibilities. To make the data science master’s programs even more flexible, edX offers part- and full-time options, and makes all materials accessible around the world.

Master of data science jobs

There are many different types of career opportunities within the data science field, with many graduates leveraging their new-found technical expertise to succeed in industries that include biotech, energy, finance, government, health care, or manufacturing. This skill set allows organizations to maximize efficiency, grow customer relationships, and reach business goals.

Businesses depend on skilled data scientists to communicate the insights they gather and help develop a plan of action for implementing decisions. They work closely with different stakeholders within an organization, often employing a multifaceted approach to their work that values both quantitative and qualitative abilities.

Employees and other professionals with data science expertise are often among the most valued members for their capability of offering indispensable business and organizational skills, as well as their ability to communicate a possible strategy and a path forward. Possible data science job titles include:

• Business analyst

• Computer information scientist

• Data analyst

• Data architect

• Data engineer

• Operations research and systems analyst

• Software developer

• Technical integration analyst

• Solutions engineer

What are the highest data science salaries?

Data science salaries may vary based on location, employer, job title, and industry. A candidate’s qualifications and collective years of experience may open the door for management positions, which typically command higher pay than more entry-level positions. Depending on the organization, there may also be an available sign-on bonus.

The median annual wage for data scientists was more than $100,000 in 2022. However, the highest 10% of data science professionals earned nearly $175,000.¹

How to become a data scientist online

While there is no single pathway to a successful career in data science, the process involves acquiring relevant knowledge and a robust skill set that will enable you to help solve some of the world’s most pressing challenges and communicate solutions in an efficient and engaging manner.

A number of data science professionals enter the workforce with education and training in computer science, statistics, or engineering. Those who study data science specifically, or a related discipline, also may work in healthcare, building statistical models that support clinical decision-making.

While there is no widely accepted minimum education requirement for becoming a data scientist, a combination of technical and non-technical skills may help along the way, and graduate programs can help professionals acquire them. A data science foundation from working on open source or on personal projects, as well as volunteer work, can come in handy, too. Critical thinking is a crucial skill set, especially if rooted in the desire to innovate, solve problems, collaborate, and be productive.

Ultimately, your career path will depend on personal goals, interests, and educational background. Being intellectually curious, attentive to detail, proactive in solving problems, and eager to learn new skills are just a few examples of personal traits that will help professionals be more effective in the workplace, master core competencies, and keep up with new developments in the field.