Medium AI Risk Slow Growth

Mathematicians

SOC Code: 15-2021

Mathematicians carries a 34% AI exposure score (Medium automation risk), with a median annual wage of $121,680 and -0.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 2,400 workers. Full task breakdown, skills, and employer data are below.

AI Exposure Score
34% Medium

Proportion of tasks susceptible to AI automation (O*NET analysis)

Projected Growth
-0.7%
2024–2034 (BLS)
+0 jobs
Median Annual Wage
$121,680
BLS May 2024
How wage figures are sourced →

AI Exposure vs Industry Growth

Workforce demand by occupation Sanctioned bespoke signature viz (@signature-viz, KIZ-799) showing occupation-level workforce demand from BLS OEWS data. Pure SVG, no external dependencies.Projected Growth 2024-2034 (BLS)Technology+12.8%Healthcare+10.2%Professional+7.8%Education+5.8%Construction+4.5%Finance+4.6%Logistics+3.2%Government+1.2%Manufacturing-2.1%Retail-3.4%
National AI Exposure
40%
Average across all occupations
Avg Wage Growth
+3.2%
Median annual wage change
High-Risk Roles
127
Occupations with >70% AI exposure

Total occupations tracked

832

Covering all SOC major groups

Data currency

2024

BLS Employment Projections

AI exposure avg

40%

Fleet-wide median across all roles

Methodology confidence 92.0%
Industry standard

Composite score weighing O*NET task data completeness, BLS projection methodology, and cross-validation with employer risk grades.

Employment Projections

2,400
Employment 2024
2,400
Projected 2034
-0.7%
Change (%)
+0
Change (jobs)

Occupation Insight

Mathematicians (SOC 15-2021) carries an AI exposure score of 34%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.

The economic context matters alongside the risk score. BLS counted approximately 2,400 workers in this occupation in 2024, and projects a -0.7% change through 2034 — a decline that often compounds with high AI exposure to create displacement headwinds. Median annual compensation stands at $121,680, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires Master's degree, plus None of related experience.

For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Mathematicians. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.

Education & Entry Requirements

Typical Education
Master's degree
Work Experience
None
On-the-Job Training
None

Top Tasks (O*NET)

  1. 1. Mentor others on mathematical techniques.
  2. 2. Maintain knowledge in the field by reading professional journals, talking with other mathematicians, and attending professional conferences.
  3. 3. Develop new principles and new relationships between existing mathematical principles to advance mathematical science.
  4. 4. Disseminate research by writing reports, publishing papers, or presenting at professional conferences.
  5. 5. Assemble sets of assumptions, and explore the consequences of each set.
  6. 6. Perform computations and apply methods of numerical analysis to data.
  7. 7. Address the relationships of quantities, magnitudes, and forms through the use of numbers and symbols.
  8. 8. Conduct research to extend mathematical knowledge in traditional areas, such as algebra, geometry, probability, and logic.
  9. 9. Develop mathematical or statistical models of phenomena to be used for analysis or for computational simulation.
  10. 10. Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields.

Key Skills Required

  • Mathematics
  • Critical Thinking
  • Reading Comprehension
  • Active Learning
  • Complex Problem Solving
  • Judgment and Decision Making
  • Writing
  • Science
  • Active Listening
  • Speaking

Knowledge Areas

  • Mathematics
  • Education and Training
  • Computers and Electronics
  • English Language
  • Physics
  • Engineering and Technology
  • Communications and Media
  • Administration and Management
  • Design
  • Administrative

Frequently Asked Questions

Will AI replace Mathematicians?

Mathematicians has an AI exposure score of 34%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.

What is the job outlook for Mathematicians?

According to BLS Employment Projections 2024-2034, Mathematicians is projected to decline by 0.7% over the decade. Current employment stands at approximately 2,400 workers.

What skills are needed for Mathematicians?

Key skills for Mathematicians include Mathematics, Critical Thinking, Reading Comprehension, and others. Typical entry-level education is Master's degree.

How much do Mathematicians earn?

The median annual wage for Mathematicians is $121,680, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.

What education is required for Mathematicians?

The typical entry-level education for Mathematicians is Master's degree. Employers generally expect None of related work experience. On-the-job training typically involves None. Requirements can vary by employer and specialization.

Which companies employ Mathematicians?

Mathematicians roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.

AI Exposure Rating

1.7
out of 5.0

Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.

Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).

Related

Data sourced from official public datasets. See our methodology for details. Retrieved and formatted by PlainWorkforce Editorial