Mathematical science teachers, postsecondary
SOC Code: 25-1022
Mathematical science teachers, postsecondary carries a 36% AI exposure score (Medium automation risk), with a median annual wage of $79,350 and +2.3% projected employment growth from 2024 to 2034 (BLS), affecting approximately 58,900 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 36% AI exposure, Mathematical science teachers, postsecondary sits 1 points below the 37.2% average across 832 U.S. occupations - more exposed than 56% of them. Most of its core tasks still require human judgment.
Career outlook score
57/100
Mathematical science teachers, postsecondary, 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 B+ $79,350
Annual median wage, percentile rank vs all tracked occupations
- Projected growth D +2.3%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) D 36% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not 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).
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 Mathematical science teachers, postsecondary in the Medium band.
Credential × growth standing
Graduate credential among the thinner entry shelves
Mathematical science teachers, postsecondary is in the Graduate band (113 of 832) with BLS pace Average (378/832). Graduate entry is a minority shelf - pairing it with average growth is the standing that separates this SOC from bachelor-dominated neighbors.
Where Mathematical science teachers, postsecondary sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Mathematical science teachers, postsecondary sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
36% Around the middle lower than 44% 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.
Mathematical science teachers, postsecondary vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Mathematical science teachers, postsecondary is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Mathematical science teachers, postsecondary'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 25-1022) 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 Mathematical science teachers, postsecondary 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 Mathematical science teachers, postsecondary. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Compile, administer, and grade examinations, or assign this work to others.
- 2. Evaluate and grade students' class work, assignments, and papers.
- 3. Prepare and deliver lectures to undergraduate or graduate students on topics such as linear algebra, differential equations, and discrete mathematics.
- 4. Maintain student attendance records, grades, and other required records.
- 5. Prepare course materials, such as syllabi, homework assignments, and handouts.
- 6. Plan, evaluate, and revise curricula, course content, and course materials and methods of instruction.
- 7. Maintain regularly scheduled office hours to advise and assist students.
- 8. Initiate, facilitate, and moderate classroom discussions.
- 9. Conduct research in a particular field of knowledge and publish findings in books, professional journals, or electronic media.
- 10. Keep abreast of developments and technological advances in the mathematical field by reading current literature, talking with colleagues, and participating in professional conferences.
Key Skills Required
- Mathematics
- Speaking
- Reading Comprehension
- Active Listening
- Instructing
- Writing
- Critical Thinking
- Learning Strategies
- Monitoring
- Active Learning
Knowledge Areas
- Mathematics
- Education and Training
- English Language
- Computers and Electronics
- Customer and Personal Service
- Administration and Management
- Physics
- Psychology
- Personnel and Human Resources
- Administrative
Frequently Asked Questions
Will AI replace Mathematical science teachers, postsecondary?
Mathematical science teachers, postsecondary has an AI exposure score of 36%, 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 Mathematical science teachers, postsecondary?
According to BLS Employment Projections 2024-2034, Mathematical science teachers, postsecondary is projected to grow by 2.3% over the decade. Current employment stands at approximately 58,900 workers.
What skills are needed for Mathematical science teachers, postsecondary?
Key skills for Mathematical science teachers, postsecondary include Mathematics, Speaking, Reading Comprehension, and others. Typical entry-level education is Doctoral or professional degree.
How much do Mathematical science teachers, postsecondary earn?
The median annual wage for Mathematical science teachers, postsecondary is $79,350, 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 Mathematical science teachers, postsecondary?
The typical entry-level education for Mathematical science teachers, postsecondary is Doctoral or professional 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 Mathematical science teachers, postsecondary?
Mathematical science teachers, postsecondary 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
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 Mathematical science teachers, postsecondary: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (36% here).
- Amusement and recreation attendants · AI exposure 36%
- Communications teachers, postsecondary · AI exposure 36%
- Computer network support specialists · AI exposure 36%
- Computer numerically controlled tool operators · AI exposure 36%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+2.3% here).
- Agricultural workers, all other · growth +2.3%
- Concierges · growth +2.3%
- First-line supervisors of landscaping, lawn service, and groundskeeping workers · growth +2.3%
- Helpers--installation, maintenance, and repair workers · growth +2.3%
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.
Related Occupations
Showing 6 of 57 occupations with a comparable automation-risk profile.
What to do with this
Use Mathematical science teachers, postsecondary's numbers above to compare, not just read in isolation.
- Compare Mathematical science teachers, postsecondary side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
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).