Biology AI Data Specialist - Remote

YO AI Labs; Miami (FL); Remote; USD 83,000 - 165,000; Part time

Job summary

YO AI Labs seeks a Biology Expert in a remote contract to critically evaluate biology-related data used in AI development workflows and to create refined scientific scenarios reflecting real-world biology.

You will provide expert-level insights to ensure accuracy of AI training datasets, collaborate with platform teams, and document methodologies to promote transparency and reproducibility in project deliverables.

Qualifications

• PhD in biology or closely related life science discipline.
• Excellent written and verbal communication of complex biology topics.
• Experience with scientific data analysis and critical evaluation of research.

Responsibilities

• Critically evaluate and provide detailed feedback on biology-related data, prompts, or content used in AI development workflows.
• Create and refine scientific scenarios, questions, or explanations reflecting real-world biological problems.
• Offer expert-level insights to ensure accuracy and depth of AI training datasets and outputs in biology.
• Collaborate with platform teams to clarify ambiguities and improve data quality in biological subject matter.
• Document findings, methodologies, and rationale to support transparency and reproducibility in project deliverables.
• Participate in iterative review cycles to enhance AI system capabilities in biology.
• Engage in knowledge-sharing sessions with interdisciplinary experts to enrich project outcomes.

Skills

Biology expertise

Scientific writing

Data analysis

Independent work

Interdisciplinary collaboration

Communication skills

Education

PhD in biology

Job description

YO AI Labs seeks a Biology Expert in a remote contract to critically evaluate biology-related data used in AI development workflows and to create refined scientific scenarios reflecting real-world biology.

You will provide expert-level insights to ensure accuracy of AI training datasets, collaborate with platform teams, and document methodologies to promote transparency and reproducibility in project deliverables.