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Becoming a Data Scientist: Skills and Education Requirements in the U.S.

The typical U.S. entry route to data science is a bachelor's degree in mathematics, statistics, computer science, or a related field, supported by strong math, programming, and communication skills. Here is what BLS says about education, skills, graduate degrees, and the 2025–2035 outlook.
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To become a data scientist in the United States, the typical entry point is a bachelor’s degree in mathematics, statistics, computer science, or a related field, backed by substantial quantitative and programming preparation. Some employers require or prefer a master’s or doctoral degree, and some specialized roles expect industry experience or coursework. The guidance below comes from U.S. Bureau of Labor Statistics (BLS) occupational materials and applies to U.S. employers only.

The typical entry route: a bachelor’s degree

BLS’s career guidance for the occupation states:

“Data scientists typically need at least a bachelor’s degree in mathematics, statistics, computer science, or a related field to enter the occupation.”

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BLS’s occupational profile also names business and engineering among common degree fields. In practice, several academic routes can prepare you for the work. The source does not say that any single major is mandatory for every employer, so treat the degree field as flexible and focus on the preparation described below.

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Mathematics and statistics preparation

BLS treats quantitative training as the core of the preparation, and it breaks that training into two stages.

In secondary school

  • Linear algebra
  • Calculus
  • Probability and statistics

At the college level

  • Computer science, in addition to mathematics and statistics

BLS does not specify a course sequence, a degree program, or an online course. Choose coursework that gives you real depth in these areas rather than a single introductory class in each.

Programming and software skills

BLS says data scientists must learn data-oriented programming languages, along with statistical software, database software, and software for presenting analyses. The source does not name a specific language or vendor tool. Because of that, the article does not treat any one language as required. If you are choosing where to start, decide based on the job listings and tools used in the sector you want to enter, and confirm that choice against current postings.

Skills employers look for

BLS’s occupational profile lists six skill areas. The table summarizes what each one covers in BLS’s description of the work.

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Skill area What BLS describes
Analytical Research, examine, and interpret findings
Computer Write code, analyze data, develop or improve algorithms, and use data visualization tools
Communication Convey analysis to technical and nontechnical audiences and make business recommendations
Logical thinking Understand and develop statistical models and analyze data
Math Use statistical methods to collect and organize data
Problem solving Address data collection and cleaning challenges, and develop statistical models and algorithms

BLS’s 2025–35 skills table ranks three skills at the top for data scientists: mathematics, computers and information technology, and writing and reading. These are BLS skill categories, not an exhaustive employer checklist.

BLS’s skill data are based on O*NET information, and BLS scores 17 skills for occupations that have published projections. That detail matters if you compare skill rankings across occupations, because the scores come from a shared framework rather than from data scientists alone.

When graduate education matters

Some employers require or prefer a master’s or doctoral degree. BLS does not establish that every data scientist needs graduate school, and it does not quantify how many jobs require one. Use the following questions to judge whether a graduate degree is worth pursuing for your target path:

  1. Math and statistics depth: Does your undergraduate program cover linear algebra, calculus, and probability and statistics in enough depth for the roles you want?
  2. Computer science and programming: Have you built working experience with data-oriented languages and database tools, not only coursework?
  3. Domain coursework or experience: Does your target sector expect knowledge of a specific field, such as finance?
  4. Employer expectations: Do the employers you are targeting list a graduate degree as required, preferred, or not mentioned?

BLS supports these four dimensions for comparing preparation routes, but it does not rank degree programs or individual providers.

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Industry experience and employer-specific requirements

BLS notes that some employers require industry-related experience or education. Its example is data scientists seeking roles at asset management companies, who may need finance experience or coursework that shows knowledge of investments, banking, or related subjects.

BLS’s 2025 education and training assignment for the occupation lists a bachelor’s degree as typical entry education. It lists no related work experience and no typical on-the-job training. That is a typical assignment for the occupation as a whole. It does not mean that no individual job asks for prior experience, and specialized postings should be read on their own terms.

U.S. outlook and pay

The figures below come from BLS’s 2026 projection release and its 2026 Occupational Outlook Handbook profile. The Handbook page was last modified August 27, 2026.

  • Projected employment growth: 35 percent from 2025 to 2035. The Handbook rounds this figure; the underlying BLS skills and projections table gives 34.6 percent. Cite the rounded figure only with its BLS presentation and period.
  • Annual openings: About 24,800 on average over 2025–35.
  • Employment level: 275,600 data scientist jobs in 2025.
  • Median annual wage: $120,230 in May 2025. This is the median for the occupation as a whole, not a starting salary for new graduates.

Projections describe the occupation’s expected trajectory. They do not guarantee employment for any individual.

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Scope of this guidance

  • The education, skills, and labor-market details come from U.S. Department of Labor sources. They should not be extended to other countries without separate evidence.
  • BLS does not publish exact employer screening rates, so this article cannot say how often a given degree or credential passes a hiring filter.
  • No specific certification is established as required for data scientists in this guidance.

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