As of June 2026, Statistician has an AI-exposure score of 57/100 (Elevated exposure) on the AI-Safe Careers index, blending O*NET tasks, the Anthropic Economic Index, the Penn/OpenAI study, and BLS data. This is an estimate of task exposure, not a prediction of job loss.
AI Exposure Score for
Statistician
57/100
Elevated exposure
LowModerateElevatedHighVery High
More exposed than 53% of the roles we track. Median pay ~US$99,000.
Pay & demand figures are US medians (BLS, in USD) — your local figures will differ. Your exposure score applies broadly.
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How you compare to similar Technology roles
Statistician (you)
57
DevOps Engineer
57
Software Developer
57
Cloud Engineer
57
Data Scientist
56
Backend Developer
59
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Your tasks, by AI exposure
Automatable
- Run statistical analyses
Augmentable
- Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
- Report results of statistical analyses, including information in the form of graphs, charts, and tables.
- Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
- Evaluate sources of information to determine any limitations, in terms of reliability or usability.
- Apply sampling techniques, or use complete enumeration bases to determine and define groups to be surveyed.
- Design studies and sampling
- Plan data collection methods for specific projects, and determine the types and sizes of sample groups to be used.
- Report results of statistical analyses in peer-reviewed papers and technical manuals.
- Develop software applications or programming for statistical modeling and graphic analysis.
- Process large amounts of data for statistical modeling and graphic analysis, using computers.
- Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.
- Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.
- Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
- Design research projects that apply valid scientific techniques, and use information obtained from baselines or historical data to structure uncompromised and efficient analyses.
- Identify relationships and trends in data, as well as any factors that could affect the results of research.
- Develop and test experimental designs, sampling techniques, and analytical methods.
- Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
Durable
- Interpret and communicate results
- Advise on methodology
Safer adjacent roles
YOUR ROLE TODAY
Statistician 57→
Data Scientist
56
82% skills overlap · Elevated exposure · ~US$108,020
Data Analyst
59
74% skills overlap · Elevated exposure · ~US$83,640
Risk Analyst
58
66% skills overlap · Elevated exposure · ~US$85,000
Biostatisticians
61
56% skills overlap · Elevated exposure · ~US$105,650
Mathematicians
59
48% skills overlap · Elevated exposure · ~US$126,710
Clinical Data Managers
76
40% skills overlap · Very High exposure · ~US$120,230
Bioinformatics Scientists
59
40% skills overlap · Elevated exposure · ~US$98,920
Operations Research Analysts
60
40% skills overlap · Elevated exposure · ~US$88,940
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Every task scored with what to do about it · 5–10 safer roles with salary, demand & reachability · skill-gap map · a 30/60/90-day roadmap · plus a résumé & LinkedIn rewrite · PDF.
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Workers with AI skills earn a roughly 62% wage premium — adapting pays. — PwC Global AI Jobs Barometer, 2026
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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.
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