Statisticians
Computer and Mathematical Occupations- O*NET-SOC 代码
- 15-2041.00
Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to provide usable information. May specialize in fields such as biostatistics, agricultural statistics, business statistics, or economic statistics. Includes mathematical and survey statisticians.
- 数据来源: BLS发布时间: 2026-08
很高· 相对
低四级相对区间很高职业群单位数值
尺度 · 母数 · 来源
四级相对类别(低 / 中等 / 高 / 很高)
以BLS就业预测表中831个细分职业为基数。取值按 NEM(全国就业矩阵)代码给定,因此共用同一 NEM 代码的职业得到相同分档
- 数据来源: Anthropic发布时间: 2026-03
0.211
0.000此处所载数值的范围0.745职业群单位数值
尺度 · 母数 · 来源
- 数据来源: ILO发布时间: 2025
0.56
0.09此处所载数值的范围0.70职业群单位数值
尺度 · 母数 · 来源
生成式AI暴露度指数,按发布原值0–1
按 ISCO-08 细类(4 位)发布的数值。按原样应用美国劳工统计局(BLS)的官方对照表(ISCO-08→2010 SOC、2010 SOC→2018 SOC)关联到本职业,对应关系为全部或部分对应
该来源发布的是什么性质的数值
BLS的类别是相对排位而非绝对水平,也不是一手测量:它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测,不是采用概率,也不区分自动化与增强。
Task-level exposure
显示隐藏的 6 项工作已评分任务 19 项 · β ≥ 0.5 的任务 19 项(100.0%)
β = 直接暴露(E1)+ 0.5 × 借助工具时的暴露(E2),依据原始代码库的定义。
- 原始单位:O*NET 27.2 任务 → O*NET 31.0 职业代码
- 所有已评分任务均在 O*NET 31.0 任务列表中。
- 来源
- OpenAI "GPTs are GPTs" exposure rubric
- 版本
- gh-main-0471612
- 许可
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 20.1) | Claude.aiRaw / share % |
|---|---|
Evaluate sources of information to determine any limitations in terms of reliability or usability.15-2041.00 | 0.399543.5 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.15-2041.00 | 0.099810.9 |
Develop an understanding of fields to which statistical methods are to be applied to determine whether methods and results are appropriate.15-2041.00 | 0.093910.2 |
Report results of statistical analyses, including information in the form of graphs, charts, and tables.15-2041.00 | 0.07588.2 |
Process large amounts of data for statistical modeling and graphic analysis, using computers.15-2041.00 | 0.05746.2 |
Identify relationships and trends in data, as well as any factors that could affect the results of research.15-2041.00 | 0.05345.8 |
Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.15-2041.00 | 0.05055.5 |
Develop software applications or programming to use for statistical modeling and graphic analysis.15-2041.00 | 0.03664.0 |
Design research projects that apply valid scientific techniques and use information obtained from baselines or historical data to structure uncompromised and efficient analyses.15-2041.00 | 0.02192.4 |
Report results of statistical analyses in peer-reviewed papers and technical manuals.15-2041.00 | 0.02172.4 |
Develop and test experimental designs, sampling techniques, and analytical methods.15-2041.00 | 0.00480.5 |
Present statistical and nonstatistical results using charts, bullets, and graphs in meetings or conferences to audiences such as clients, peers, and students.15-2041.00 | 0.00390.4 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task (O*NET 27.2) | βE1 + 0.5 × E2 |
|---|---|
Process large amounts of data for statistical modeling and graphic analysis, using computers.O*NET Task ID 8954 | 1.0 |
Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.O*NET Task ID 8957 | 1.0 |
Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.O*NET Task ID 8958 | 1.0 |
Supervise and provide instructions for workers collecting and tabulating data.O*NET Task ID 8963 | 1.0 |
Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.O*NET Task ID 8965 | 1.0 |
Develop and test experimental designs, sampling techniques, and analytical methods.O*NET Task ID 8966 | 1.0 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.O*NET Task ID 8967 | 1.0 |
Develop software applications or programming for statistical modeling and graphic analysis.O*NET Task ID 20193 | 1.0 |
Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.O*NET Task ID 20194 | 1.0 |
Determine whether statistical methods are appropriate, based on user needs or research questions of interest.O*NET Task ID 21100 | 1.0 |
Prepare and structure data warehouses for storing data.O*NET Task ID 21101 | 1.0 |
Report results of statistical analyses, including information in the form of graphs, charts, and tables.O*NET Task ID 8953 | 0.5 |
Identify relationships and trends in data, as well as any factors that could affect the results of research.O*NET Task ID 8955 | 0.5 |
Analyze and interpret statistical data to identify significant differences in relationships among sources of information.O*NET Task ID 8956 | 0.5 |
Evaluate sources of information to determine any limitations, in terms of reliability or usability.O*NET Task ID 8959 | 0.5 |
Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used.O*NET Task ID 8960 | 0.5 |
Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses.O*NET Task ID 8961 | 0.5 |
Apply sampling techniques, or use complete enumeration bases to determine and define groups to be surveyed.O*NET Task ID 8964 | 0.5 |
Report results of statistical analyses in peer-reviewed papers and technical manuals.O*NET Task ID 20192 | 0.5 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
O*NET 31.0 全部任务(19 项)
本职业在 O*NET 31.0 中的全部任务(英文原文;任务类型为核心或补充)。暴露值不列在此清单中,而在上方表格里,位于各来源所用 O*NET 版本的任务表述旁。
| 任务(O*NET 31.0) | 类型 |
|---|---|
| Report results of statistical analyses, including information in the form of graphs, charts, and tables. | 核心 |
| Process large amounts of data for statistical modeling and graphic analysis, using computers. | 核心 |
| Identify relationships and trends in data, as well as any factors that could affect the results of research. | 核心 |
| Analyze and interpret statistical data to identify significant differences in relationships among sources of information. | 核心 |
| Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data. | 核心 |
| Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy. | 核心 |
| Evaluate sources of information to determine any limitations, in terms of reliability or usability. | 核心 |
| Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used. | 核心 |
| Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses. | 核心 |
| Supervise and provide instructions for workers collecting and tabulating data. | 核心 |
| Apply sampling techniques, or use complete enumeration bases to determine and define groups to be surveyed. | 核心 |
| Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering. | 核心 |
| Develop and test experimental designs, sampling techniques, and analytical methods. | 核心 |
| Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data. | 核心 |
| Report results of statistical analyses in peer-reviewed papers and technical manuals. | 核心 |
| Develop software applications or programming for statistical modeling and graphic analysis. | 核心 |
| Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students. | 核心 |
| Determine whether statistical methods are appropriate, based on user needs or research questions of interest. | 核心 |
| Prepare and structure data warehouses for storing data. | 补充 |
0.00/ 3· 机器人暴露指数
尺度 · 母数 · 来源
对每项体力任务,按已实际部署、销售或演示的机器人能够完成它的环境评定 0–3 级(0 不可 · 1 围栏式机器单元、灌装线等机器人专用设施 · 2 医院药房、集装箱港口等受管理的设施 · 3 私人住宅、建筑工地等非结构化环境),再按工作时间占比求平均
以该职业 O*NET 29.3 任务中的体力任务为准
等级与时间占比由 Anthropic 使用 Claude Opus 5(网络搜索)估算(截至 2026 年)。
机器人暴露指数与本站的 AI 暴露度是不同的指标,不能相加或相互比较。该指数不代表实际采用情况或成本竞争力,0 也包括没有体力任务的职业。
每项体力任务的等级
该职业的 O*NET 29.3 任务中没有被归类为体力任务的任务。
职业信息
就业展望(BLS)
这些数值属于整个 SOC 15-2041 组(Statisticians),并非仅属于该 O*NET 职业。
- 就业人数,2025
- 31K
- 预计就业人数,2035
- 35K
- 变化 (2025–35)
- +11%
- 年薪中位数,2025
- $105,650
- 入职通常所需学历
- Master's degree
韩国职业分类关联(KSCO)
来自 AI Changing Work 制作的 Korea Occupation Direct Crosswalk v1.1 当前版本的关联。关系值从 O*NET-SOC 职业一侧解读。
| KSCO 代码 | KSCO 名称 | 关系 | 状态 |
|---|---|---|---|
| 21123 | 수학 및 통계학 연구원 | 本职业范围更窄 | 已确认 |
关系与状态的定义(kr-direct v1.1)
国际劳工组织(ILO)职业说明
以下 ISCO-08 职业组由 AI Changing Work 原样套用美国劳工统计局(BLS)发布的对照表(2018 SOC→2010 SOC、2010 SOC→ISCO-08)、不逐案取舍,与本职业相关联;每项关联可能是完全对应,也可能是部分对应。
- ISCO-08 2120Mathematicians, Actuaries and Statisticians
数学家、精算师和统计学家
自行翻译
自行翻译 · 非 ISCO 官方词汇 — 未经国际劳工组织审核。
以下定义、任务和职业示例是 ILO 对该 ISCO-08 职业组的描述,而不是对本职业的描述。
Mathematicians, actuaries and statisticians conduct research and improve or develop mathematical, actuarial and statistical concepts, theories and operational methods and techniques and advise on or engage in their practical application in such fields as engineering, business and social and other sciences.
任务
- (a) studying, improving and developing mathematical, actuarial and statistical theories and techniques;
- (b) advising on or applying mathematical principles, models and techniques to a wide range of tasks in the fields of engineering, natural, social or life sciences;
- (c) conducting logical analyses of management problems, especially in terms of input-output effectiveness, and formulating mathematical models of each problem usually for programmeming and solution by computer;
- (c) designing and putting into operation pension schemes and life, health, social and other types of insurance systems;
- (e) applying mathematics, statistics, probability and risk theory to assess potential financial impacts of future events;
- (f) planning and organizing surveys and other statistical collections, and designing questionnaires;
- (g) evaluating, processing, analysing, and interpreting statistical data and preparing them for publication;
- (h) advising on or applying various data collection methods and statistical methods and techniques, and determining reliability of findings, especially in such fields as business or medicine as well as in other areas of natural, social or life sciences;
- (i) preparing scientific papers and reports;
- (j) supervising the work of mathematical, actuarial and statistical assistants and statistical clerks.
职业示例
Actuary · Demographer · Mathematician · Operations research analyst · Statistician
Sources: ILO ISCO-08 — details: Credits
ESCO 职业词汇
以下每一项都是在已公开的ESCO-O*NET Crosswalk(第 1 版,2022 年)中与本职业逐项对应的。对应类型出自该对照表;表述出自 AI Changing Work。
- statisticianESCO 2120.6范围相同
Statisticians collect, tabulate, and, most importantly, analyse quantitative information coming from a varied array of fields. They interpret and analyse statistical studies on fields such as health, demographics, finance, business, etc. and advise based on patterns and drawn analysis.
- biometricianESCO 2120.6.1本职业范围更宽
Biometricians perform research in the field of biometrics. They carry statistical or biological research projects by measuring fingerprints, retinas, and human shapes for medical or industrial applications.
- data scientistESCO 2511.3有重叠,但不相同
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
- statistical assistantESCO 3314.2有重叠,但不相同
Statistical assistants collect data and use statistical formulas to execute statistical studies and create reports. They create charts, graphs and surveys.
来源: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
许可: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
法国职业分类关联(ROME)
本职业与 ROME 4.0 职业条目(fiche)之间的关联,由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。标为「暂定」的关联仅凭同一模型系列(Claude)两位判定者的判定采纳,或对其判定适用运营方规则后采纳,因此其依据弱于已确认的关联。
| ROME 代码 | ROME 名称(法语) | 关系 |
|---|---|---|
| M1414 | Ingénieur statisticien / Ingénieure statisticienne | 范围相同暂定 |
| K2403 | Biostatisticien / Biostatisticienne | 本职业范围更宽暂定 |
| M1403 | Chargé / Chargée d'études socio-économiques | 有重叠,但不相同暂定 |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
西班牙职业分类关联(CNO-11)
本职业与 CNO-11 职业之间的关联,由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。
| CNO-11 代码 | CNO-11 名称(西班牙语) | 关系 |
|---|---|---|
| 2416 | Estadísticos | 范围相同 |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
德国职业分类关联(KldB)
本职业与 KldB 职业之间的关联,由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。
| KldB 代码 | KldB 名称(德语) | 关系 |
|---|---|---|
| 41114 | Berufe in der Statistik - hoch komplexe Tätigkeiten | 范围相同 |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
日本职业分类关联(JSCO)
本职业与 JSCO 职业之间的关联,由 AI Changing Work 借助 AI 模型判定。关系从本职业一侧解读。
| JSCO 代码 | JSCO 名称(日语) | 关系 |
|---|---|---|
| 051 | 自然科学系研究者 | 相关,但不对应 |
| 052 | 人文・社会科学系等研究者 | 相关,但不对应 |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
本页数据的来源与许可,以及 AI Changing Work 的修改与翻译说明:致谢与来源