Remote Computational Public Health Researcher: AI Evaluator

DataAnnotation; North Carolina; Remote; USD 55,000 - 172,000; Full time

Job summary

DataAnnotation is a remote, project-based role for experienced computational biologists and bioinformaticians to train AI models. You will design realistic analysis tasks from your own workflows, run them through frontier AI agents, and grade the deliverables against professional standards.

You will also write clear grading rubrics and explain why a response passes or fails, flag concrete failures with evidence, and apply your expertise across genomics, transcriptomics, proteomics, and ML

Qualifications

• 3+ years hands-on analyzing real biological data in industry, an academic lab, or a research institute (counted after undergraduate study).
• Proficient in Python and/or R (at least one required, both preferred).
• Depth in at least one area: genomics, transcriptomics, proteomics/metabolomics, population genetics, ML in biology, or related fields.
• End-to-end multistep analysis experience from raw data to interpretation; able to judge real results.
• Master’s or PhD (or current candidate) completed in the U.S., Canada, Europe, or the UK.
• Excellent written English; comfortable with ambiguity; familiarity with AI/LLM tools like Claude or ChatGPT.

Responsibilities

• Design realistic analysis tasks from your own workflows: the scenario, the prompt, and the necessary files (count matrices, sample sheets, VCFs, logs, QC).
• Run tasks through frontier AI agents and grade the deliverable against professional standards.
• Write clear grading rubrics and explain why a response passes or fails.
• Flag concrete failures with evidence: ignored batch effects, wrong statistical tests, uncorrected p-values, or misused references.

Skills

Python

R

English writing

Documentation

Education

Master's or PhD in biology or bioinformatics

Tools

Claude

ChatGPT

Job description

DataAnnotation is a remote, project-based role for experienced computational biologists and bioinformaticians to train AI models. You will design realistic analysis tasks from your own workflows, run them through frontier AI agents, and grade the deliverables against professional standards.

You will also write clear grading rubrics and explain why a response passes or fails, flag concrete failures with evidence, and apply your expertise across genomics, transcriptomics, proteomics, and ML