Remote AI Pharmacologist Trainer in Genomics

DataAnnotation; Canada; Remote; CAD 117,000 - 244,000; Full time

Benefits offered by this job

Flexible remote work

Project-based work

Job summary

DataAnnotation is seeking experienced computational biologists and bioinformaticians to design realistic analysis tasks from their own practice and run them through frontier AI systems. You will grade outputs against professional standards and write clear rubrics, explaining why a result passes or fails.

Responsibilities include flagging concrete failures with evidence such as batch effects, inappropriate tests, and misused references, ensuring rigorous interpretation of results.

Qualifications

• 3+ years hands-on analyzing real biological data in industry, an academic lab, or a research institute.
• Proficient in Python and/or R (at least one).
• Depth in genomics and variant interpretation; transcriptomics or multiomics; ML applied to biology.
• Owned a multistep analysis end to end, from raw data to interpretation.
• Master's or PhD in biology, bioinformatics, biostatistics, CS or related field (US/Canada/Europe/UK).
• Clear written English and comfort with ambiguity.
• Based in US, Canada, or the UK (Ireland/Australia may be accepted).

Responsibilities

• Design realistic analysis tasks from your workflows, specifying the scenario, prompts, and necessary files.
• 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 (batch effects, wrong tests, misused reference versions, dropped samples).

Skills

Python

R

Written English

Education

Master's or PhD in biology or related field

Tools

Claude

ChatGPT

Job description

DataAnnotation is seeking experienced computational biologists and bioinformaticians to design realistic analysis tasks from their own practice and run them through frontier AI systems. You will grade outputs against professional standards and write clear rubrics, explaining why a result passes or fails.

Responsibilities include flagging concrete failures with evidence such as batch effects, inappropriate tests, and misused references, ensuring rigorous interpretation of results.