Remote Data Scientist: AI Review & Validation Expert

AI Trainer Jobs; United States; Remote; USD 138,000 - 207,000; Full time

Job summary

AI Trainer Jobs is seeking contractors for a remote Data Scientist Talent Network role. The project involves evaluating AI outputs across research science reasoning, calculations, and workflows, with emphasis on reproducing key results and documenting correct methods to aid model training.

Ideal candidates hold PhD/postdoc or equivalent research experience, have published or taught at a professional level, and can reliably allocate at least 10 hours per week in a flexible async schedule.

Qualifications

• Graduate-level training or equivalent applied experience in research science or a closely related field for Data Scientist Talent Network work.
• Hands-on experience publishing, teaching, or advising on the topic at a professional level.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that cites methods, papers, or worked examples.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current research science methods, conventions, and prior work for Data Scientist Talent Network assignments.
• Reproduce or sanity-check key derivations, calculations, or experimental claims.
• Flag dimensional, methodological, and citation errors with structured severity tags.
• Capture the corrected reasoning or worked example so the modeling team can train on it.

Skills

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Research science

Education

PhD, postdoc, or industry research experience

Job description

AI Trainer Jobs is seeking contractors for a remote Data Scientist Talent Network role. The project involves evaluating AI outputs across research science reasoning, calculations, and workflows, with emphasis on reproducing key results and documenting correct methods to aid model training.

Ideal candidates hold PhD/postdoc or equivalent research experience, have published or taught at a professional level, and can reliably allocate at least 10 hours per week in a flexible async schedule.