Remote Climate Data Scientist - AI Training Specialist

Alignerr Corp.; España; Presencial; EUR 73.000 - 133.000; A tiempo parcial

Descripción de la vacante

Alignerr is seeking Climate Data Specialists (Masters/PhDs) to design real-world environmental science problems that train AI models to think like experts. This is a fully remote hourly contract with 10–40 hours per week, inviting researchers to apply domain knowledge at scale.

Ideal candidates hold advanced degrees in environmental sciences, are proficient in Python or R, and can work asynchronously in a remote setting.

Formación

• Hold a Master's or PhD in Environmental Science, Climate Science, Ecology, or a closely related field.
• Deeply knowledgeable in climate modeling, ecology, sustainability, or adjacent areas.
• Proficient in Python or R — whether from research, academic projects, or professional work.
• A precise, clear communicator who takes scientific accuracy seriously.
• Self-directed and comfortable working asynchronously in a remote environment.
• Fluent in English and based in the U.S., Canada, U.K., Australia, or New Zealand.

Responsabilidades

• Design and develop advanced, real-world environmental science problems spanning climate modeling, ecology, sustainability, and related disciplines
• Solve and review complex problem sets to ensure scientific accuracy, rigor, and depth
• Apply your domain expertise to challenge and improve AI model reasoning across environmental topics
• Collaborate asynchronously with AI researchers and fellow domain experts to refine outputs
• Ensure all deliverables meet high standards of clarity, scientific integrity, and intellectual depth

Conocimientos

Python

R

Scientific communication

Asynchronous collaboration

Educación

Master's or PhD in Environmental Science or related field

Herramientas

Python

R

Descripción del empleo

Alignerr is seeking Climate Data Specialists (Masters/PhDs) to design real-world environmental science problems that train AI models to think like experts. This is a fully remote hourly contract with 10–40 hours per week, inviting researchers to apply domain knowledge at scale.

Ideal candidates hold advanced degrees in environmental sciences, are proficient in Python or R, and can work asynchronously in a remote setting.