Computer and Mathematical · United States (national)
Biostatisticians
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is highly exposed to automation, and the bigger shift looks near-term.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 62.0 to 86.0
Physical / roboticsrange 0.0 to 24.0
When the change is likely
Near-term, highlocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Act within the next 1 to 2 years
Displacement for this role is near-term. Start a concrete reskilling plan now, while you still have income and leverage.
2
Lean into the human edge
The exposed parts are routine and cognitive. Invest in judgment, client relationships, and complex problem-solving that AI still cannot do.
3
Pivot toward Bioinformatics Scientists
It is skill-adjacent and less exposed (54.5 vs 74). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
Keep the monitor on
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Task-by-task exposure breakdown
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Which of my tasks are exposed
Draw conclusions or make predictions, based on data summaries or statistical analyses.
50.0
Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.
50.0
Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
50.0
Calculate sample size requirements for clinical studies.
74.0
Read current literature, attend meetings or conferences, and talk with colleagues to keep abreast of methodological or conceptual developments in fields such as biostatistics, pharmacology, life sciences, and social sciences.
50.0
Design research studies in collaboration with physicians, life scientists, or other professionals.
50.0
Prepare tables and graphs to present clinical data or results.
74.0
Write program code to analyze data with statistical analysis software.
50.0
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Calculate sample size requirements for clinical studies.
Task: Prepare tables and graphs to present clinical data or results.
Lower-risk adjacent roles
Bioinformatics Scientists
54.5
Clinical Data Managers
57.5
Data Scientists
59.4
Bioinformatics Technicians
65.0
Statistical Assistants
67.4
Statisticians
71.0
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map Biostatisticians to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 74.0, robotics 12.0.
The timeline comes from the higher axis (74.0), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.