BestOnlineCollege.org is an advertising-supported website. Many of the school and program listings that appear on this site are from partners who compensate us, and this compensation may affect how, where, and in what order listings appear (such as featured placements). This compensation does not influence our editorial content, evaluations, or rankings, which are determined independently using publicly available data. We do not review or feature every school or program available in the marketplace. Our goal is to provide accurate, unbiased information so you can make informed decisions. Read our full Advertiser Disclosure.
How to Become a Data Scientist: Degree & Salary (2026)
Key takeaway: There is no license or certification exam for data science. You become a data scientist by acquiring three things and being able to prove them: statistics, programming with SQL, and finished analyses someone can inspect. A bachelor's degree is the typical entry-level education the Bureau of Labor Statistics lists for the occupation, and many postings ask for a master's. Data Scientists earned a median annual wage of $120,230 (Bureau of Labor Statistics, May 2025 OEWS), and employment is projected to grow 33.5 percent from 2024 to 2034 with 23,400 openings per year (BLS Employment Projections, 2024-2034).
View the data behind this chart
| Percentile | Annual wage |
|---|---|
| 10th percentile | $67,240 |
| 25th percentile | $85,660 |
| Median | $120,230 |
| 75th percentile | $158,880 |
| 90th percentile | $199,130 |
Data science is one of the fields on this site with no legal gate. No state board licenses data scientists. No exam confers the title. What replaces the credential is evidence: work someone can read, plus the ability to answer technical questions about why you did it that way.
A degree is the most reliable way to build that evidence, especially the mathematics, which is the part self-taught entrants most often skip. It is not the only way, and plenty of working data scientists hold degrees in physics, economics, biology, or computer science instead.
This path is for analysis and modeling work. If the job you want is dashboards, reporting, and business metrics, that is data analytics. If it is building software, that is computer science or software engineering.
Step-by-step: how to become a data scientist
-
Build the mathematics. Calculus, linear algebra, and a probability and statistics sequence. This is the foundation everything else sits on, and it is the hardest part to assemble later. Regression, dimensionality reduction, and most machine learning are linear algebra and probability wearing different names. If you are short, community college coursework in calculus and linear algebra is the cheapest fix and it tests your interest before you commit.
-
Learn to program, and learn SQL properly. Python or R for analysis, and SQL for getting the data in the first place. SQL is the most common technical screen in hiring and the most commonly underestimated skill: joins across imperfect keys, window functions, and query performance are daily work. Add version control early, because your coursework will become your portfolio.
-
Choose a degree path, if you want one. An online bachelor’s in data science supplies the math and computing core inside a four-year credential, and it is the typical entry-level education BLS lists. An online master’s is the common route for career changers who hold a degree in another field and for analysts moving toward modeling. Verify institutional accreditation through the U.S. Department of Education database; ABET accredits a small number of data science bachelor’s programs, and its absence is normal.
-
Learn modeling and, more importantly, evaluation. Regression, classification, cross-validation, regularization, and ensembles are the toolkit. The part that separates candidates is evaluation: knowing why your validation split leaks, why the test metric flatters the model, and when a simpler model is the right answer. Add experimental design and causal inference if the program offers them, because deciding whether something caused something is most of the value in industry analysis.
-
Finish projects on messy real data. Two or three complete analyses beat eight notebooks. Each should state the question, the data and its limitations, the method, the evaluation, and what you would do differently. Use data that arrived dirty, since cleaning is a large share of the job and interviewers know it. Publish them where a hiring manager can read them.
-
Practice the interview loop deliberately. A typical process includes a SQL screen, a statistics or modeling conversation, a take-home or case study, and a presentation of your reasoning to a non-technical audience. Each of those is a separate skill. The presentation is the one technical candidates most often lose on.
-
Enter through the nearest door. Many data scientists start with an analyst title and move across as the portfolio grows. Others enter through a domain they already know, which is an advantage rather than a compromise: a nurse who learns data science is more valuable in health analytics than a generalist. Related occupations to consider include Statisticians at a median annual wage of $105,650 and Operations Research Analysts at $88,940 (Bureau of Labor Statistics, May 2025 OEWS).
What degree do you need to be a data scientist?
None is legally required. In practice:
- A bachelor’s degree is what BLS lists as the typical entry-level education for the occupation. It can be in data science, statistics, computer science, mathematics, or another quantitative field.
- An online bachelor’s in data science is the most direct undergraduate route and packages the math, the programming, and a capstone together.
- An online master’s in data science is most valuable for career changers and for analysts moving into modeling. Many research-facing postings ask for it.
- A doctorate is a research apprenticeship. Choose it for research roles, not as a shortcut to a senior industry title.
- No degree is workable if you already have quantitative training from elsewhere and can demonstrate the skills. The obstacle is the recruiter screen rather than the work itself.
Related fields worth comparing before you commit: statistics for inference depth, mathematics for theory, machine learning and artificial intelligence for model building, and the data science vs data analytics comparison if you are undecided between the two.
How much do data scientists make?
Data Scientists earned a national median annual wage of $120,230 (Bureau of Labor Statistics, May 2025 OEWS). Half earned more and half earned less. The spread is wide: the 10th percentile was $67,240 and the 90th percentile was $199,130 (Bureau of Labor Statistics, May 2025 OEWS). Employment was 245,900 in 2024, projected to grow 33.5 percent through 2034 with 23,400 openings per year (BLS Employment Projections, 2024-2034). Expect a first job nearer the lower percentiles, and note that the range reflects both experience and the fact that the title covers several different jobs.
Neighboring occupations for people who take a different door into the same skill set: Software Developers earned a median annual wage of $135,980 with 115,200 openings per year, Database Architects $139,500, Actuaries $130,000, Computer Systems Analysts $105,850, Statisticians $105,650, Operations Research Analysts $88,940, and Market Research Analysts and Marketing Specialists $78,760 (Bureau of Labor Statistics, May 2025 OEWS; BLS Employment Projections, 2024-2034). See what you can do with a data science degree for the job-by-job detail.
How long does it take to become a data scientist?
There is no clock that confers the title. There are clocks on the credentials and on skill building.
| Phase | Typical duration |
|---|---|
| Building the math foundation | Two to four semesters of coursework, depending on where placement puts you |
| Bachelor’s degree | About 4 years from scratch; shorter with transfer credit (approximately 120 semester hours) |
| Master’s degree | Varies by program and credit total; add bridge coursework if prerequisites are missing |
| Building a portfolio | Ongoing; the first two solid projects usually take a few months |
| First role | Often entered through an analyst or domain title rather than a data scientist title |
These are ranges rather than guarantees. Catalogs set credit totals; employers set their own bars.
Frequently asked questions
What degree do you need to be a data scientist?
None is legally required. The Bureau of Labor Statistics lists a bachelor’s degree as the typical entry-level education for Data Scientists, and many postings ask for a master’s, particularly for research-facing and modeling-heavy work. Quantitative degrees in statistics, computer science, and mathematics are common alternatives to a data science major.
Do you need to be certified to be a data scientist?
No. There is no state license and no professional certification that authorizes the work. Vendor certificates from cloud and analytics platforms can signal tool familiarity, but they do not replace the mathematics and they are not accreditation. Institutional accreditation matters when choosing a degree program.
How long does it take to become a data scientist?
A bachelor’s from scratch is typically about four years, less with transfer credit. A master’s varies by program and by how much bridge coursework you need. Neither timeline includes the portfolio, which you build alongside the degree rather than after it.
How much do data scientists make?
Data Scientists earned a national median annual wage of $120,230, with the 10th percentile at $67,240 and the 90th at $199,130 (Bureau of Labor Statistics, May 2025 OEWS). Entry-level pay is well below the median, and the wide range partly reflects how many different jobs share the title.
Is data science a good career?
Employment is projected to grow 33.5 percent from 2024 to 2034, with 23,400 openings per year (BLS Employment Projections, 2024-2034), the fastest projected growth among the occupations associated with this degree. Growth describes an occupation, not an individual outcome, and competition for entry-level roles is real. See is an online data science degree worth it.
Can I become a data scientist without a math background?
You can start without one, but you cannot finish without one. Calculus, linear algebra, and probability are what the methods are made of, and technical interviews test whether you understand them. A program that does not require them is training you to operate tools rather than to choose them.
Related guides
- Online Data Science Degrees Guide – the full hub covering degree levels and formats
- Online Bachelor’s in Data Science – the math and computing core inside a four-year degree
- Online Master’s in Data Science – prerequisites, capstone, and who the degree fits
- What Can You Do With a Data Science Degree? – the associated occupations with BLS wages
- How to Become a Data Analyst – the reporting-focused path
- How to Become a Statistician – the inference-focused path
- Data Science Programs by State – find programs near you
Wage figures on this page come from the U.S. Bureau of Labor Statistics Occupational Employment and Wage Statistics (May 2025 national medians) and Employment Projections (2024-2034).
Data verified: September 5, 2026. Salary, employment, and tuition figures on this page are sourced from the U.S. Bureau of Labor Statistics (OEWS May 2025; Employment Projections 2024–2034) and the U.S. Department of Education College Scorecard (2023 cohort). The source agency and data year are cited inline with every statistic.