Data Scientist Talent Network

AuraOne; United States; On-site; 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

Data Scientist Talent Network is a remote review track for evaluating AI outputs across research science reasoning, calculations, and research workflows. Reviewers grade derivations and assumptions, reproduce key results, and document the correct method so the modeling team can train on it.

Category: Scientific AI & Domain Experts · Pay: $100–$150 / hr · Location: Remote — US-eligible · Contractor

Data Scientist Talent Network is a remote review track for evaluating AI outputs across research science reasoning, calculations, and research workflows.

Role details

About the role

Data Scientist Talent Network is a remote review track for evaluating AI outputs across research science reasoning, calculations, and research workflows. Reviewers grade derivations and assumptions, reproduce key results, and document the correct method so the modeling team can train on it.
Research science models live or die on whether their derivations actually hold up under scrutiny. AuraOne uses scientific specialists to grade outputs the way a peer reviewer would — checking assumptions, reproducing key steps, and capturing the right method alongside the wrong one.
Bring scientific and technical domain expertise into AI reasoning, research, and dataset review.

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.

What you should bring

• 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.

Role signals

Example tasks

• Reproduce a research science derivation from a model output and flag any algebraic or dimensional errors.
• Grade a model's literature summary against the cited papers and rate the citation quality.
• Adjudicate a disputed answer between two reviewers using textbook methods.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Useful experience

• PhD, postdoc, or industry research experience in the topic area.
• Prior work reviewing AI-assisted research tooling and its failure modes.
• Multilingual fluency for non-English papers and corpora.

Compensation and schedule

$100–$150 / hr
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Scientific reasoning
• Method validation
• Citation review
• Quantitative analysis
• Research science