# Cytogenetic Technologists

> Analyze chromosomes or chromosome segments found in biological specimens, such as amniotic fluids, bone marrow, solid tumors, and blood to aid in the study, diagnosis, classification, or treatment of inherited or acquired genetic diseases. Conduct analyses through classical cytogenetic, fluorescent in situ hybridization (FISH) or array comparative genome hybridization (aCGH) techniques.

- **SOC code:** 29-2011.01
- **Canonical URL:** https://singulariki.com/roles/role-29-2011-01
- **Also known as:** Clinical Cytogeneticist Scientist (CCS), Cytogenetic Technologist, Cytogenetics Clinical Laboratory Specialist (CG CLSp), Molecular Genetics Technologist, Certified Cytogenetic Technologist, Cytogenetics Technical Specialist, Cytogenetics Technologist, Cytogenetic Technician
- **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):
- Count numbers of chromosomes and identify the structural abnormalities by viewing culture slides through microscopes, light microscopes, or photomicroscopes.
- Arrange and attach chromosomes in numbered pairs on karyotype charts, using standard genetics laboratory practices and nomenclature, to identify normal or abnormal chromosomes.
- Examine chromosomes found in biological specimens to detect abnormalities.
- Apply prepared specimen and control to appropriate grid, run instrumentation, and produce analyzable results.
- Harvest cell cultures using substances such as mitotic arrestants, cell releasing agents, and cell fixatives.
- Analyze chromosomes found in biological specimens to aid diagnoses and treatments for genetic diseases such as congenital disabilities, fertility problems, and hematological disorders.
- Select appropriate culturing system or procedure based on specimen type and reason for referral.
- Summarize test results and report to appropriate authorities.
- Prepare biological specimens such as amniotic fluids, bone marrow, tumors, chorionic villi, and blood, for chromosome examinations.
- Select or prepare specimens and media for cell cultures using aseptic techniques, knowledge of medium components, or cell nutritional requirements.
- Communicate test results or technical information to patients, physicians, family members, or researchers.
- Prepare slides of cell cultures following standard procedures.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Biology _(knowledge)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Information Ordering _(ability)_
- Near Vision _(ability)_
- Reading Comprehension _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Oral Expression _(ability)_
- Deductive Reasoning _(ability)_
- Inductive Reasoning _(ability)_
- Writing _(essential_skill)_
- Written Expression _(ability)_

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

**Tools & technology:**
- Adobe Illustrator _(hot technology)_
- C++ _(hot technology)_
- Microsoft Excel _(hot technology)_
- Microsoft Office software _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Word _(hot technology)_
- Python _(hot technology)_
- Cell Bioscience Automated Image Capture
- Digital karyotyping software
- Genetix CytoVision
- Genial Genetics iPassport QMS

## AI exposure & outlook

- **AI task-overlap index:** 53rd percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 56th percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 53rd percentile (Moderate) — source: eloundou_gamma.
- **Frey–Osborne (2013, historical computerization estimate):** 78th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **“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-29-2011-01_