# Biostatisticians

> Develop and apply biostatistical theory and methods to the study of life sciences.

- **SOC code:** 15-2041.01
- **Canonical URL:** https://singulariki.com/roles/role-15-2041-01
- **Also known as:** Biometrician, Biostatistician, Research Scientist, Statistical Scientist, Biostatistical Consultant, Bioinformatics Scientist, Biomathematician, Clinical Biostatistician
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Draw conclusions or make predictions, based on data summaries or statistical analyses.
- Analyze clinical or survey data, using statistical approaches such as longitudinal analysis, mixed-effect modeling, logistic regression analyses, and model-building techniques.
- Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
- Calculate sample size requirements for clinical studies.
- 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.
- Prepare tables and graphs to present clinical data or results.
- Design research studies in collaboration with physicians, life scientists, or other professionals.
- Write program code to analyze data with statistical analysis software.
- Provide biostatistical consultation to clients or colleagues.
- Review clinical or other medical research protocols and recommend appropriate statistical analyses.
- Prepare statistical data for inclusion in reports to data monitoring committees, federal regulatory agencies, managers, or clients.
- Determine project plans, timelines, or technical objectives for statistical aspects of biological research studies.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Mathematics _(essential_skill)_
- Inductive Reasoning _(ability)_
- Mathematical Reasoning _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Deductive Reasoning _(ability)_
- Reading Comprehension _(essential_skill)_
- Speaking _(essential_skill)_
- Science _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Active Learning _(essential_skill)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Active Learning _(Common Skill)_
- Writing _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- English Language _(Common Skill)_
- Active Listening _(Common Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- IBM SPSS Statistics _(hot technology, in demand)_
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Python _(hot technology, in demand)_
- R _(hot technology, in demand)_
- SAP software _(hot technology, in demand)_
- SAS _(hot technology, in demand)_
- Structured query language SQL _(hot technology, in demand)_
- Bash _(hot technology)_
- C# _(hot technology)_
- C++ _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 99th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 95th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 92nd percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 34th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 8.5% growth (Growing fast); 2k annual openings; 32.2k → 34.9k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $103,300; 29,800 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 44% automation, 46% augmentation (usage-weighted).
- **Autonomy median:** 3.0 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Prepare articles for publication or presentation at professional conferences. _(3.0% of measured AI use; task iteration)_
- Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports. _(2.9% of measured AI use; directive)_
- Write program code to analyze data using statistical analysis software. _(2.6% of measured AI use; directive)_
- Draw conclusions or make predictions based on data summaries or statistical analyses. _(1.0% of measured AI use; directive)_
- 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. _(0.9% of measured AI use; learning)_
- Collect data through surveys or experimentation. _(0.4% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me prepare articles for publication or presentation at professional conferences.
- Help me write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.
- Help me write program code to analyze data using statistical analysis software.
- Help me draw conclusions or make predictions based on data summaries or statistical analyses.
- Help me 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.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-15-2041-01_