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Gathering salary data, outlook, and education paths
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Starting Salary
Median Salary
Top Earners
Job Growth
Professionals in USA

Career Overview

Mathematicians develop new mathematical theories, methods, and models, or apply existing mathematical techniques to solve real-world problems in fields like engineering, finance, cryptography, and data science. Their work ranges from highly abstract theoretical research conducted in academia to applied problem-solving within government agencies, tech companies, and financial institutions.

Salary Range (US, estimates)

Entry level$62,000
Median$112,000
Senior$145,000
Top 10%$180,000

Key Statistics

Job growth+11%
Professionals in the USA0.03 million
Typical hours/week40 hrs
Remote work share35%
Annual job openings2,900/yr
DemandModerate

Education Paths

  • Required minimum: Bachelor's Degree in Mathematics — Provides foundational knowledge in calculus, algebra, and statistics, sufficient for some entry-level applied roles.
  • Most common: Master's or PhD in Mathematics — Advanced degrees are typically required for research positions and most professional 'mathematician' job titles in government and industry.
  • Accelerator: Programming & Data Science Skills — Proficiency in Python, R, or MATLAB significantly broadens job prospects into data science, quantitative finance, and machine learning roles.

Core Skills

  • Abstract and analytical reasoning
  • Advanced calculus and algebra
  • Statistical modeling
  • Programming (Python, R, MATLAB)
  • Problem formulation and proof writing
  • Data analysis and interpretation

Pros

  • Intellectually stimulating and creative work
  • High earning potential in specialized fields like finance or data science
  • Wide applicability across industries (tech, research, government)
  • Opportunities for remote or academic flexible work

Cons

  • Highly competitive academic job market
  • Requires extensive education (often a PhD)
  • Can be isolating or abstract with limited real-world feedback
  • Risk of skill obsolescence without continuous learning in computational tools

AI Impact on This Career

AI and computational tools are transforming mathematics by automating routine calculations, symbolic manipulation, and even assisting in proof verification. However, the core work of formulating novel problems, developing theoretical frameworks, and applying deep conceptual reasoning remains firmly human-driven.

Automation exposure: Numerical computation, symbolic algebra, data cleaning, routine statistical analysis, and pattern detection in large datasets are increasingly automated through tools like Mathematica, MATLAB, and AI-assisted theorem provers.

The human edge: Mathematicians excel at creative problem formulation, intuition-driven conjecture, abstract reasoning across disciplines, and understanding the 'why' behind mathematical structures—areas where AI still lacks genuine insight and creativity.

Figures are estimates for exploration — verify current data with BLS.gov.