Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.

Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields. is a detailed work activity in O*NET — a concrete unit of work shared across 8 occupations and seen in 12 occupation-specific tasks. It rolls up into the broader work activity Analyze scientific or applied data using mathematical principles. in Analyzing Data or Information .

Detailed work activities are the most granular shared layer in O*NET's work-activity hierarchy (Generalized → Intermediate → Detailed → occupation-specific task). The figures below describe how this activity shows up across the economy and what independent studies measure about AI and this kind of work — not a prediction that the work will be automated.

AI exposure

Of the 12 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 12 (100%) are flagged as directly exposed to language models (E1) or exposed via model-powered tools (E2).

The Anthropic Economic Index observes real AI use on 6 of these tasks, with a mean mapped-usage share of 0.028% per task.

Exposure estimates overlap with model capabilities — whether a model could speed the task up — not whether the work will be done by software. Observed AI use is augmentation and assistance today, not jobs replaced.

Member tasks

Occupation-specific tasks O*NET maps to this detailed work activity, most important first.

• Define data requirements, and gather and validate information, applying judgment and statistical tests. · Operations Research Analysts · importance 4.5 · exposure with tools
• Perform complex calculations as part of the analysis and evaluation of data, using computers. · Physicists · importance 4.3 · direct LLM exposure
• Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering. · Statisticians · importance 4.3 · direct LLM exposure
• Compile laboratory test data and perform appropriate analyses. · Quality Control Analysts · importance 4.2 · exposure with tools
• Break systems into their components, assign numerical values to each component, and examine the mathematical relationships between them. · Operations Research Analysts · importance 3.7 · direct LLM exposure
• Apply mathematical theories and techniques to the solution of practical problems in business, engineering, the sciences, or other fields. · Mathematicians · importance 3.7 · direct LLM exposure
• Apply research or simulation results to extend biological theory or recommend new research projects. · Biostatisticians · importance 3.6 · exposure with tools
• Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design. · Software Developers · importance 3.6 · direct LLM exposure
• Develop or use mathematical models to track changes in biological phenomena, such as the spread of infectious diseases. · Biostatisticians · importance 3.5 · exposure with tools
• Calculate orbits and determine sizes, shapes, brightness, and motions of different celestial bodies. · Astronomers · importance 3.3 · exposure with tools
• Compare models using statistical performance metrics, such as loss functions or proportion of explained variance. · Data Scientists · direct LLM exposure
• Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques. · Data Scientists · direct LLM exposure

Occupations that perform this

• Operations Research Analysts
• Physicists
• Statisticians
• Quality Control Analysts
• Mathematicians
• Software Developers
• Astronomers
• Data Scientists

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-apply-mathematical-principles-or-statistical-approaches-to-solve-problems-in-scientific-or-applied-fields,
  title  = {Apply mathematical principles or statistical approaches to solve problems in scientific or applied fields.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/detailed-activities/apply-mathematical-principles-or-statistical-approaches-to-solve-problems-in-scientific-or-applied-fields}
}