Remote Computational Biologist: AI Task Designer & Evaluator

DataAnnotation; United States; Remote; USD 55,000 - 172,000; Full time

Job summary

DataAnnotation is seeking experienced computational biologists and bioinformaticians to design and evaluate AI training tasks. You will create realistic analysis challenges from your own practice, run them through frontier AI systems, and judge outputs against a rigorous standard.

You will write rubrics detailing normalization, multiple-testing corrections, and biological interpretation, and highlight failures with solid evidence.

Qualifications

• 3+ years hands-on analyzing real biological data in industry, an academic lab, or a research institute.
• You write, debug, and can explain your own analysis code in Python and/or R (at least one required, both preferred).
• Depth in at least one: genomics and variant interpretation; bulk or single-cell transcriptomics; proteomics/metabolomics/multiomics; population and statistical genetics; ML applied to biology; clinical genomics; metagenomics or phylogenetics.

Responsibilities

• Design realistic analysis tasks from your own workflows: the scenario, the prompt, and the files an agent would need (count matrices, sample sheets and metadata, VCFs, pipeline logs and QC output, analysis notebooks).
• Run tasks through frontier AI agents and grade the deliverable against a professional standard.
• Write clear grading rubrics and explain why a response passes or fails.
• Flag concrete failures with evidence: batch effects, wrong statistical test, uncorrected p-values, misused reference version, dropped samples, or code that doesn’t do what the narrative claims.

Skills

Clear written English

Education

Master’s or PhD in biology or bioinformatics

Tools

Python

R

Job description

DataAnnotation is seeking experienced computational biologists and bioinformaticians to design and evaluate AI training tasks. You will create realistic analysis challenges from your own practice, run them through frontier AI systems, and judge outputs against a rigorous standard.

You will write rubrics detailing normalization, multiple-testing corrections, and biological interpretation, and highlight failures with solid evidence.