Do you need a masters or PhD to work in data science?
Written by: Shelby Campbell, Edited by: Valerie Black
Published: March 13, 2025
With the growth of new artificial intelligence (AI) technology, data scientists are among the most highly sought-after employees on the job market. In fact, the Bureau of Labor Statistics (BLS) projects that employment for data scientists will grow by 36% from 2023-33, which is nine times higher than average and one of the highest projected growth rates of any career.
But does your dream data science role require a master's degree, or PhD? In this guide, learn what you need to succeed in this hot field.
Industry demands for data scientists
Data scientists collect and analyze data to draw conclusions. As a data scientist, your day-to-day work may involve finding new sources of raw data, organizing and visualizing it, and conducting tests using algorithms and databases. These tests can reveal insights that help business leaders better understand a market or consumer base.
According to the BLS, data scientists earned a median annual salary of $108,020 in May 2023. Additionally, BLS data projects a 36% job growth for data science jobs between 2023–33. Much of this increase is likely to come from the development of AI and machine learning technology.
Data science is integral to AI functions. Machine learning programs, which are a type of AI, determine outcomes by extracting trends and probability from the data. As a result, data scientists are increasingly necessary to find usable datasets, develop algorithms that probe the data, and assess the algorithm's effectiveness.
Pathways to getting into the data science field
Getting a job in data science requires high-level knowledge of mathematics, statistics, and programming. You generally need experience that proves your proficiency in these subjects to get hired, even in entry-level jobs.
While some companies ask that applicants have a master's or PhD, many only require a bachelor's degree in subjects like mathematics, computer science, or statistics. Data from Lightcast shows that 57% of data scientist job postings request at least a bachelor's degree, 28% request a master's, and 11% request a Ph.D.
| Master's level | PhD level |
|---|---|
| Programming | Research delivery |
| Data visualization | Legal compliance |
| The ethics of data science | Data interaction |
| Linear algebra and statistics | Computation cognitive monitoring |
| Algorithmic development | Time-dependent probability |
Find the right data science courses for you
Balancing self-study and formal education
Although an advanced degree in data science can garner lots of attention from potential employers, not everyone has the time or money to earn one. But you don't have to give up your dream of becoming a data scientist — many programs, including the MITx MicroMasters® data science and statistics program offered on edX — combine self-study and flexible traditional education to give your résumé the boost you need to get hired.
MicroMasters programs focus on helping working professionals gain new skills and qualify for higher-paying positions. Additionally, MicroMasters programs can be applied for credits in 50+ graduate degree programs, including a PhD at the Massachusetts Institute of Technology (MIT) and a master's at Harvard University, if you are admitted to those programs.
Because machine learning technology is progressing so rapidly, data scientists may need to continuously gain skills as the field evolves. MicroMasters programs can help you stay up-to-date with trends and advancements without committing to an advanced degree program.
Conclusion
Data science is a growing field with a high demand for skilled workers. While a master's degree or PhD in data science can help you stay competitive in the job market, you can also enhance your résumé by gaining practical skills through work experience and nontraditional education.
Sign up for a data science course on edX today and discover how flexible education can provide a pathway to new opportunities.