The Highest-Paying Data Careers in the U.S. and the Skills Employers Require

Scope and method: This guide compares eight U.S. occupations involving data analysis, database systems, quantitative risk or computing research. They are ordered by national median annual wages for May 2025, using U.S. Bureau of Labor Statistics profiles checked on 5 November 2026. The highest-paying roles below are the highest within this selected group, not an exhaustive ranking of every data-related job. Management and general software-engineering occupations are outside this comparison.

A median marks the midpoint of earnings in an occupation. These figures cover workers at different experience levels, exclude self-employed workers and are neither starting salaries nor total-compensation offers. Research-scientist and mathematician figures cover the whole BLS occupation, not just its data-focused specialists.

Eight data-related careers, compared on the same basis

1. Computer and information research scientists: $140,300. This occupation includes developing algorithms and conducting computing experiments, sometimes using machine learning. BLS highlights advanced mathematics, logical reasoning, research evaluation and explaining findings. A relevant master’s degree is typical, although some federal roles accept a bachelor’s. Research-scientist duties and preparation.
2. Database architects: $139,500. Architects turn organisational requirements into database designs and integrate systems. Database languages such as SQL, technical problem-solving and communicating with developers matter. A relevant bachelor’s degree is typical; employers may require certification in their database products. Database architecture and administration requirements.
3. Actuaries: $130,000. Actuaries analyse the financial consequences of risk. Preparation combines mathematics, statistics and business knowledge with spreadsheets, databases and statistical tools. A bachelor’s degree is typical, and professional certification requires examinations. BLS says many employers expect prospective hires to have passed one or two exams before graduation. Actuarial education and certification.
4. Mathematicians: $126,710. Mathematical modelling and computational methods support practical problem-solving across industries. Relevant skills include calculus, linear algebra, programming and explaining technical conclusions. BLS lists a master’s degree as typical for mathematicians and statisticians, with some bachelor’s-level positions available. Mathematics and statistics career profile.
5. Data scientists: $120,230. Core work includes extracting insights, writing code, developing models and presenting results. Data cleaning, statistical reasoning, visualisation and communicating recommendations are central skills. A relevant bachelor’s degree is typical, while some employers require or prefer advanced degrees or industry knowledge. Data-science skills and education.
6. Statisticians: $105,650. Statisticians help determine what data to collect, design studies and evaluate results. Sampling, statistical software, model development and explaining uncertainty distinguish this work from simply producing charts. The shared BLS mathematics and statistics profile explains education and duties, but reports the two occupations’ wages separately.
7. Database administrators: $104,620. Administration focuses on keeping databases usable, secure and reliable. SQL, troubleshooting, permissions, backups and restoration connect directly to the work. Some responsibilities overlap with architecture, but the occupations have separate pay figures. Read the BLS database profile before treating either title as interchangeable.
8. Operations research analysts: $88,940. Analysts use quantitative methods to investigate decisions and recommend solutions. Mathematics, statistical and database software, forecasting and communicating trade-offs are useful foundations. At least a bachelor’s degree is typical, with some positions requiring a master’s. Operations research preparation.

Translate occupational skills into employer requirements

BLS describes typical preparation across an occupation. An individual employer decides which tools, experience and qualifications its vacancy requires. A useful next step is to compare several current advertisements on employers’ own career sites for the same role, location and seniority.

• Separate requirements from preferences. Record mandatory qualifications in one column and desirable extras in another. Keep degree, examination and experience requirements separate from software keywords.
• Read the duties before matching the title. “Data engineer” or “analytics manager” should not automatically inherit the database-architect median. Note whether the work centres on building infrastructure, interpreting evidence, conducting research or managing people.
• Look for repeated, concrete work. Compare requests such as maintaining production databases, validating models or presenting recommendations. Count distinct vacancies rather than repeated copies of the same advertisement.
• Choose evidence you can demonstrate. As a preparation exercise, document a tested backup-and-restore process for database work or an analysis explaining sampling limitations for statistics. These are suggested work samples, not substitutes for required qualifications.

Use pay as one part of the decision

Compare local advertised ranges, working arrangements and responsibilities before judging an opportunity. Ask how bonuses, equity and benefits are treated rather than comparing a complete offer directly with a national wage median. Choose a path whose daily work and preparation requirements fit you, then use repeated vacancy requirements to decide what to learn next.