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
Typical exposure

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

Projected Growth
-0.7%
Typical growth
2024–2034 (BLS)
+0 jobs
Median Annual Wage
$121,680
Top 10% pay
BLS May 2024
How wage figures are sourced →
The verdict

At 34% AI exposure, Mathematicians sits 3 points below the 37.2% average across 832 U.S. occupations - more exposed than 43% of them. Most of its core tasks still require human judgment.

34%
AI exposure
43rd
percentile
-0.7%
Job growth 2024–34
$121,680
Median wage
C

Career outlook score

59/100

Mathematicians, weighted across 3 of 3 tracked dimensions

A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.

  • Median wage A+ $121,680

    Annual median wage, percentile rank vs all tracked occupations

  • Projected growth F -0.7%

    Projected employment change, 2024-2034, BLS Employment Projections

  • AI exposure (inverted) C 34% exposure

    Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure

Employment vs AI exposure

Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).

4.3M
Home health and personal care aides employment (#1)
#392
Home health and personal care aides AI rank
95%
Bookkeeping, accounting, and auditing clerks AI exposure (#1)
#17
Bookkeeping, accounting, and auditing clerks employment rank

Automation-risk inventory

Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Mathematicians in the Medium band.

Credential × growth standing

Graduate credential among the thinner entry shelves

Mathematicians is in the Graduate band (113 of 832) with BLS pace Slow growth (245/832). Graduate entry is a minority shelf - pairing it with slow growth growth is the standing that separates this SOC from bachelor-dominated neighbors.

Where Mathematicians sits among all occupations

AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.

Where Mathematicians sits by AI exposure

AI-exposure score distribution across U.S. occupations (O*NET task analysis)

34% Lower than most lower than 57% of 832 occupations

Occupations, banded by AI-exposure score

Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.

Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034

Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.

Mathematicians vs. its occupational neighbors

AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Mathematicians is marked in rose; the top-left corner is the most future-proof.

Future-proofGrowing but exposedStable, lower-AIMost at risk29.8%41.9%54%66.1%78.2%-6.1%4.3%14.6%25.0%35.4%AI exposure (%) →Projected growth (%) →Mathematicians, AI exposure (%) →: 34% · Projected growth (%) →: -0.7%MathematiciansSoftware developers, AI exposure (%) →: 45% · Projected growth (%) →: 15.8%Software developersComputer user suppor, AI exposure (%) →: 36% · Projected growth (%) →: -3.7%Computer user supporComputer systems ana, AI exposure (%) →: 44% · Projected growth (%) →: 8.7%Computer systems anaComputer occupations, AI exposure (%) →: 76% · Projected growth (%) →: 8.2%Computer occupationsNetwork, AI exposure (%) →: 32% · Projected growth (%) →: -4.2%NetworkData scientists, AI exposure (%) →: 61% · Projected growth (%) →: 33.5%Data scientistsSoftware quality ass, AI exposure (%) →: 46% · Projected growth (%) →: 10%Software quality assInformation security, AI exposure (%) →: 45% · Projected growth (%) →: 28.5%Information securityComputer network arc, AI exposure (%) →: 49% · Projected growth (%) →: 11.9%Computer network arcComputer network sup, AI exposure (%) →: 36% · Projected growth (%) →: 1.8%Computer network supWeb, AI exposure (%) →: 36% · Projected growth (%) →: 7%Web

Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).

Employment Projections

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

Where This Score Comes From

Mathematicians's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the 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 employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 15-2021) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Mathematicians be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.

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.

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.

Nationwide occupations with similar workforce profiles

Two data-derived peer sets for Mathematicians: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).

Similar AI exposure score

Nearest O*NET task-automability scores nationwide (34% here).

Similar projected growth (2024–2034)

Nearest BLS employment change rates nationwide (-0.7% here).

Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.

What to do with this

Use Mathematicians' numbers above to compare, not just read in isolation.

AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.

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).

Every figure on PlainWorkforce is rendered directly from BLS/O*NET source data, no number is typed in by an editor. See our editorial standards & corrections policy, the methodology behind these figures, or report a data error. Data current as of BLS Employment Projections 2024-2034.

Sources: BLS Employment Projections 2024-2034, O*NET Database 30.0.