Biology Expert - Remote

YO IT Consulting; España; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

YO IT Consulting is seeking a research-focused professional to critically evaluate biology-related data and prompts used in AI development workflows. You will create and review scientific scenarios reflecting complex, real-world biological problems and provide expert insights to ensure accuracy in AI training datasets.

The role emphasizes collaboration with platform teams to improve data quality and representativeness, thorough documentation of methods, and ongoing evaluation to advance the AI

Formación

• PhD in biology or closely related life science discipline is preferred.
• Strong written and verbal communication abilities.
• Experience with scientific data analysis and critical evaluation of research.

Responsabilidades

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

Conocimientos

Communication skills

Scientific data analysis

Independent work

Interdisciplinary collaboration

Educación

PhD in biology

Descripción del empleo

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

Job Description

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

Preferred Qualifications

• PhD in biology or a closely related life science discipline.
• Demonstrated expertise in core biological principles with the ability to contextualize complex topics for diverse audiences.
• Exceptional written and verbal communication skills, ensuring clear articulation of feedback and scientific reasoning.
• Experience with scientific data analysis, critical evaluation of research, and synthesis of intricate subject matter.
• Proven ability to work independently, consistently delivering high‑quality outputs within defined project frameworks.
• Prior contributions to interdisciplinary scientific or technology‑focused projects (exposure to AI is a plus but not mandatory).
• Keen attention to detail, consistency, and a passion for promoting scientific rigor and accuracy.