Remote Computational Biologist — AI Model Trainer

DataAnnotation; Iowa (LA); Remote; USD 55,000 - 172,000; Full time

Benefits offered by this job

Flexible schedule

Remote work

Job summary

DataAnnotation is seeking experienced computational biologists and bioinformaticians to help train AI models. You’ll design analysis tasks from your own practice, run them through frontier AI systems, and grade what comes back against a professional standard.

The models can discuss biology, but your role is to QC results, assess analysis quality, and provide concrete feedback. Expect remote, project-based work with emphasis on Python or R proficiency and advanced genetics knowledge.

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; able to write, debug, and explain your own analysis code.
• Depth in at least one area: genomics and variant interpretation; bulk or single-cell transcriptomics; proteomics/metabolomics/multiomics; population/genetic statistics; ML in biology; clinical genomics; metagenomics/phylogenetics.
• You’ve owned a multistep analysis end to end, from raw or messy data to final interpretation, and can judge whether a result is real.
• Master’s or PhD (or current PhD candidate) completed in the U.S., Canada, Europe, or the UK.
• Clear written English, comfort with ambiguity, and familiarity with AI/LLM tools like Claude or ChatGPT.
• Based in the United States, Canada, or the UK (Ireland and Australia may also be accepted).

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 the standard you’d hold a colleague to.
• Write clear grading rubrics (the right normalization, the right multiple-testing correction, the right biological reading) and explain why a response passes or fails.
• Flag concrete failures with evidence: batch effects and confounders ignored, wrong statistical test or uncorrected p-values, misused reference version, silently dropped samples, or code that doesn’t do what the narrative claims.

Skills

Python

R

Education

Master’s or PhD in related field

Job description

DataAnnotation is seeking experienced computational biologists and bioinformaticians to help train AI models. You’ll design analysis tasks from your own practice, run them through frontier AI systems, and grade what comes back against a professional standard.

The models can discuss biology, but your role is to QC results, assess analysis quality, and provide concrete feedback. Expect remote, project-based work with emphasis on Python or R proficiency and advanced genetics knowledge.