Genomics AI Training Scientist

DataAnnotation; Michigan; Remote; USD 55,000 - 172,000; Full time

Benefits offered by this job

Remote work

Flexible projects

Job summary

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

You’ll evaluate tasks such as QC of RNA-seq matrices, variant prioritization, batch effect diagnosis, and pipeline auditing, ensuring robust statistical methods and accurate biological interpretation.

Qualifications

• 3+ years hands-on analyzing real biological data in industry, an academic lab, or a research institute.
• Ability to write, debug, and explain analysis code in Python and/or R (at least one language required, both preferred).
• Depth in at least one of genomics/variant interpretation; bulk/single-cell transcriptomics; proteomics/metabolomics/multiomics; population/genetics; ML in biology; clinical genomics; metagenomics/phylogenetics.
• Experience owning a multistep analysis end to end, from raw data to final interpretation, and assessing result realism.
• Masters or PhD (or current PhD candidate) in biology, bioinformatics, biostatistics, CS, or related field, completed in the U.S., Canada, Europe, or the UK.

Responsibilities

• Design realistic analysis tasks from your workflows: the scenario, the prompt, and necessary files.
• Run tasks through frontier AI agents and grade the deliverable against your standard.
• Write clear grading rubrics and explain why a response passes or fails.
• Flag concrete failures with evidence (batch effects ignored, wrong tests, uncorrected p-values, misused references, dropped samples).

Skills

English proficiency

Communication

Education

Master's or PhD in biology / bioinformatics / biostatistics / CS

Tools

Python

R

Job description

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

You’ll evaluate tasks such as QC of RNA-seq matrices, variant prioritization, batch effect diagnosis, and pipeline auditing, ensuring robust statistical methods and accurate biological interpretation.