Remote Research Science Reviewer & Derivation Validator

AuraOne, Inc.; United States; Sur place; USD 83 000 - 165 000; Temps partiel

Résumé du poste

AuraOne, Inc. seeks a Competitive Data Scientist to evaluate AI outputs across research reasoning, calculations, and workflows.

This remote contractor role focuses on grading derivations, reproducing key steps, and documenting the right method for training data curation. Responsibilities include reviewing outputs against research standards, reproducing or sanity-checking claims, flagging errors, and capturing corrected reasoning to support the modeling team.

Qualifications

• Graduate-level training or equivalent applied experience in research science.
• 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.

Responsabilités

• Review AI outputs against current research science methods, conventions, and prior work for Competitive Data Scientist 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.
• Adjudicate disputed answers against textbooks, papers, or community standards.
• Maintain reviewer-quality scores in inter-rater calibration cycles.

Connaissances

Scientific reasoning

Method validation

Citation review

Quantitative analysis

Research science

Formation

PhD or equivalent research experience

Description du poste

AuraOne, Inc. seeks a Competitive Data Scientist to evaluate AI outputs across research reasoning, calculations, and workflows.

This remote contractor role focuses on grading derivations, reproducing key steps, and documenting the right method for training data curation. Responsibilities include reviewing outputs against research standards, reproducing or sanity-checking claims, flagging errors, and capturing corrected reasoning to support the modeling team.