Our Guide to Online Master’s in Data Science Programs

More than ten years after Thomas H. Davenport and DJ Patil proclaimed data scientist the “sexiest job of the 21st century” in the pages of Harvard Business Review, they revisited their proclamation to see if it still held true. Their findings? Still sexy: “The amount of data, analytics, and AI in business and society seem unlikely to decline, so the job of data scientist will only continue to grow in its importance in the business landscape.”

The US Bureau of Labor Statistics (BLS) would agree. According to BLS forecasts, the US data science job market, which has a median pay of $100,910 annually, will grow by 36% over the decade. Compare this to the numbers for the US as a whole: median pay of $45,760 in 2021 and just 5% labor market growth projected by 2031.

Despite these promising numbers, some looking to get into data science — or looking to progress along a data science career path — still hesitate to invest in traditional education paths. While an in-person data science master’s can significantly improve one’s career prospects, it’s still a time- and money-intensive pursuit. For many, these start-up costs are too much to overcome, regardless of the potential return on investment.

Luckily, there’s increasingly a more flexible path to a data science master’s: online study. Colleges and universities are offering more online data science master’s programs than ever. In this guide, we’ll dive into the details of the degree and the advantages and disadvantages of online study so you can decide for yourself if it’s the right path for you.

What is data science?

Data science leverages the tools of fields like computer science, applied mathematics, information technology, and machine learning to derive insights from big data sets and develop new tools and techniques for doing so.

Why pursue a master’s degree in data science?

Data science master’s candidates typically pursue the degree for one of two reasons: they are either looking to advance along a data science career path they’ve already started or transition into a data science career and land their first data science job.

Career advancement

Those working as a data analyst or entry-level data scientist who already have skills in programming, statistical analysis, and data management might pursue a master’s of science (MS) in data science to advance their skillset and learn new techniques, software, and best practices. Often, doing so can qualify them for promotion at their current company or a more senior role elsewhere, which brings with it higher compensation and more responsibility.

Career transition

Data science master’s programs are also frequently attended by those with bachelor’s degrees looking to change career paths. While some programs require students to have a background in STEM or facility with programming or statistical analysis, many will accept applicants with backgrounds in the social sciences or the humanities, provided they attend remedial courses in mathematics and/or computer science prior to beginning the program or at its beginning.

What kinds of jobs are available to those with master’s degrees in data science?

In addition to data science roles, a master’s in data science prepares you for a variety of related professions. Here’s how they differ.

Data scientist

A data scientist designs, develops, and deploys new methods and techniques for extracting insights from data sets, and then communicates their findings to relevant stakeholders. According to Salary.com’s real-time compensation data, the average annual salary for a data scientist in the US is $140,042.

Data architect

A data architect designs data pipelines to maximize efficiency according to a business’ particular needs, capacities, and resources. According to Salary.com, the average annual salary for a data architect in the US is $124,771.

Data engineer

While the responsibilities of data architects and data engineers can overlap, the primary distinction is that a data architect designs data pipelines while a data engineer develops and deploys them. According to Salary.com, the average annual salary for a data engineer in the US is $112,555.

Data analyst

A data analyst collects, prepares, and analyzes data to generate insights to support business operations. According to Salary.com, the average annual salary for a data analyst in the US is $81,719. Some data analysts go on to work as data scientists, data architects, data engineers, or some other advanced role. To learn more about data analyst positions, see our guides to the best master’s in data analytics program, data analytics online master’s programs, and the typical data analyst career path.

Business or business intelligence analyst

Business analysts and business intelligence analysts both utilize data analysis to serve business goals. While a business analyst focuses on analyzing data to drive decisions related to big-picture initiatives like reducing costs, maximizing revenues, or entering new markets, a business intelligence analyst focuses instead on producing intelligence tools, including reports and dashboards. According to Salary.com, a business analyst in the US earns an average salary of $85,507, while a business analyst earns an average of $80,003. To learn more about business analytics, see our explainer and our business analyst career path guide.

Machine learning engineer

A machine learning engineer designs, develops, ships, and maintains machine learning models. According to Salary.com, a machine learning engineer in the US earns an average of $121,605.

Why pursue a data science master’s degree online?

A master’s in data science can open any of the above careers to you — but why should you consider pursuing this degree online? In our eyes, an online MS in data science offers flexibility, accessibility, and cost savings over its in-person counterpart, with only very manageable downsides. But before we dive into these, let’s zoom out to consider the state of online learning as a whole.

The state of online learning

Twenty years ago, to pursue a master’s degree online was a rarity, not least because technological capabilities were not what they are today. In the two decades since, however, the market share of online programs has expanded. Data provided by Urban Institute show master’s students studying online comprising almost one-third of the total number of master’s students in 2016, up from 21% in 2012 and just 5% in 2000.

bar chart detailing masters students by program modality

Source: InsideHigherEd.com

Though it is too soon to see concrete data attesting to an acceleration in online master’s enrollment in the wake of the coronavirus pandemic, the successes of distance learning during this period, public sentiment as to the comfort of remote study, and the fact that there have simply never been more online master’s programs than ever before points at least to their continued popularity.

While improved technological capabilities certainly play a role in the rise of online master’s, they’ve gained market share also because they present certain advantages over traditional in-person programs. We’ll discuss these now.

Advantages of Online Master’s Programs

Online master’s programs appeal because they are flexible, accessible, and offer potential cost savings.

Flexibility

The ability to learn from home, either through live video-sessions or pre-recorded lectures, allows online master’s students to fit their education around busy lives. Online students can continue to work while they study, care for a loved one, or even travel. Online programs can often be taken part-time, offering even further flexibility.

Accessibility

Just as home-study offers flexibility, it offers accessibility: for many, geography and cost would otherwise keep them from studying at the best universities in the world. Online master’s degrees bring the universities to the students, while also more easily providing accommodations for those with cognitive or physical impairments such as closed captioning, on-demand video, and speech input.

Potential Cost Savings

Higher education is traditionally quite expensive in the US, and master’s degrees are no exception: according to Educationdata.org, the average master’s of science degree in the US costs $61,200. While public universities are more affordable, especially if you qualify for in-state tuition, master’s degrees still average $29,150.

While they won’t bring the cost to zero, online study offers significant savings if it means a student can forego relocation and commuting and continue working.

Disadvantages of Online Master’s Programs

The advantages of online master’s programs are substantial, but there are still disadvantages to consider as you decide whether to pursue an online degree.

No Campus Experience

For some, the experience of a college campus is a core component of their education. With online study, you’ll have to forego walking across the quad, studying in the libraries, and enjoying those cultural happenings, parties, and academic resources that are only accessible on campus.

Digital Networking

Online study almost always means digital networking. Some flourish in front of a Zoom window, but if that’s not you, then the absence of in-person networking opportunities is something to take seriously.

Potential for Lower Engagement

For some, online study can hurt engagement and motivation. Again, if this sounds like you, consider if you’ll be able to make the most of an online degree program.

Online Master’s in Data Science: Pros & Cons

Pros	Cons
More flexible	Loss of campus experience
More accessible	Limited or no in-person networking
Potential more affordable	Potential for lower engagement

What’s the curriculum of an online master’s in data science program?

The curriculum of an online master’s in data science program is much the same as the in-person equivalent. Students can expect to cover the following when studying data science online:

Computer science and information technology, including advanced courses in artificial intelligence, machine learning, data mining, and software design

Statistics, including advanced courses in exploratory data analysis and data visualization, statistical modeling, and statistical analysis with SQL and R

Data science principles, including research design, data management, applied data science, and data science ethics

Industry-specific electives such as Business Analytics, Marketing Analytics, Sports Performance Analytics, Big Data in Finance, etc.

What should you look for in an online master’s in data science program?

Having weighed the advantages and disadvantages, you’ve decided that pursuing a master’s in data science online is the right choice for you. What should you look for in a program?

Program profile

Many programs have the same basic curriculum, but they don’t all emphasize the same things. Perhaps you’re more interested in business analytics, or data mining, or artificial intelligence. Before applying for a program, you want to make sure that what it focuses on matches up with you want to.

Reputation

Reputation matters — but can you put a price on it? Name recognition is important for many recruiters, and online, it’s easier than ever to study at a big-name institution. But while these institutions might offer stellar instruction, there’s a good chance you can get a solid education for a fraction of the price at a state school (especially if you qualify for in-state tuition).

Cost

Master’s study is expensive, but it doesn’t need to be exorbitant. As you are planning how to finance your education, consider lower-priced public options, any scholarships or grants you might qualify for, lost potential income, increased earning potential from your education, as well as interest if you take out loans to fund your education. Check out our guide on the salaries master's in data science graduates can expect to help evaluate the return on education.

Career support

When researching graduate programs, pay attention to the kinds of career support they offer, such as internships, career offices, alumni networks, or private job boards. Pay attention also to any student outcome data they provide, as this data can help you calculate the potential that you’ll see a return on your investment.

Our picks for best online master’s in data science programs

There’s no single “best” online data science master’s program: each student comes from a different background and has different needs and interests. Accordingly, our picks forego ranking and instead focus on presenting a variety of great programs that we think will deliver lasting value. The factors behind our decisions include:

Reputation: Is the program’s name a significant asset?

Program profile: Does the program offer a curriculum that fits your interest and will help you not just get a job you want, but excel in it?

Career services: Are there sufficient resources to help you find a job after graduating? Are graduates getting placed in well-paying jobs?

Cost: Is there a high likelihood of substantial return on the initial investment?

With that in mind, here are our recommendations:

Johns Hopkins University

Johns Hopkins’ Data Science Master’s Program Online is geared towards the working professional interested in gaining skills in areas like machine learning, data visualization, game theory, and data systems. Students take seven required courses, two applied and computational mathematics electives, and one computer science elective. Those with existing skills who want to learn more are able to take a proficiency exam to place out of certain requirements. In addition to the master’s program, Johns Hopkins offers a graduate certificate and a post-master’s certificate in data science.

Program Highlights:

Data Engineering Principles and Practice
Big Data Processing Using Hadoop
Data Mining

Program Length & Modality: Part-time within 5 years, live online

Prerequisites & Requirements:

Three semesters of calculus
One semester of advanced mathematics
One semester of Python or Java

Tuition: Approximately $49,200

The University of Texas at Austin

UT Austin’s Master of Science in Data Science online program offers a flexible and inexpensive way to gain graduate-level training in simulation, visualization, machine learning, and optimization. While delivered through the edX platform, the materials for this online master’s program are created and supervised by UT Austin faculty and staff.

Program Highlights:

Probability and Simulation-Based Inference for Data Science
Foundations of Regression and Predictive Modeling
Reinforcement Learning

Program Length & Modality: Between 2 and 6 years, self-paced online

Prerequisites & Requirements:

Bachelor’s degree from accredited institution
3.0 GPA or higher preferred
Must demonstrate knowledge of mathematics and programming through coursework, experience and MSDS Quest Assessment

Tuition: $10,000

Northwestern University

Northwestern’s Master’s in Data Science program focuses on teaching students how to use programming languages and environments like R, Python, Go, TensorFlow, and Keras for deep learning applications to drive business growth. Students complete 12 courses in total, broken into six core courses, two specialization courses, two electives, and a capstone project. For their specialization, online students choose from one of six options: Analytics and Modeling, Analytics Management, Artificial Intelligence, Data Engineering, General Data Science, or Technology Entrepreneurship.

Program Highlights:

Database Systems and Data Preparation
Real-Time Stream Processing and Analytics
Data Governance, Ethics, and Law

Program Length & Modality: Between 2 and 5 years, live online

Prerequisites & Requirements

Aptitude or existing skill in programming and applied mathematics

Tuition: $58,860

Drexel University

Drexel’s Online Masters Degree in Data Science allows students to choose one of three possible elective tracks — Analytics, Mining, and Algorithms; Visualization and Communications; Management and Accountability — in addition to core data science courses focusing on machine learning, cloud computing, data acquisition, and more. Students also complete a capstone project.

Those holding bachelor’s degrees who don’t wish to complete a full data science degree program or who aren’t yet qualified can instead take one of Drexel’s certificate programs in applied data science, computational data science, or big data analytics.

Program Highlights:

Applied Machine Learning for Data Science
Introduction to Data Analytics
Healthcare Informatics
Disaster Recovery, Continuity Planning, and Digital Risk Assessment

Program Length & Modality: As little as 1 year, online

Prerequisites & Requirements:

Four-year bachelor’s degree. If not in Computer Science, Software Engineering, or Math, additional prerequisites may be required.
3.0 GPA preferred

Tuition: $62,820

Georgia Institute of Technology

Georgia Tech’s Online Master of Science in Analytics offers an affordable program of study from one of the nation’s top-ranked data science and data analytics programs. Students have the opportunity to complete courses in big data analytics, visual analytics, computing, and statistics at their own pace. They can also take electives online with the same professors who offer classes on campus in one of three areas of specialization: Analytical Tools, Business Analytics, or Computational Data Analytics. At the end, students complete a six-hour practicum in which they utilize what they’ve learned about applied data science and data analysis in an independent project.

Program Highlights:

Introduction for Computing for Data Analytics
Computational Data Analysis
Applied Natural Language Processing

Program Length & Modality: 24–72 months, self-paced online

Prerequisites & Requirements:

At least one course in probability, programming, or calculus and linear algebra
GRE and GMAT optional

Tuition: $9,900

What’s next?

In this guide, we dived into the basics of online masters in data science programs, discussing their core curricula, advantages and disadvantages, and what to look for when researching on your own. We’ve also presented some of our favorite programs. What’s next? If you see a program that interests you, we recommend clicking through to the program’s website so that you can request information.

If you’re interested in master’s-level data science study but not ready to pull the trigger, check out our article on whether perhaps a data science bootcamp would make financial sense for you. Alternatively, you can check out our breakdown of the costs and benefits of master’s in data analytics degrees, many of which are directly transferable to data science. are data science master’s degree makes financial sense for you.