AI Data Science Domain Expert

AI Trainer Jobs; United States; Remote; USD 117,000 - 131,000; Full time

Job summary

AuraOne is seeking a remote AI Data Science Domain Expert to evaluate AI outputs across data science domain specialist operations workflows. Reviewers assess workflow correctness, policy adherence, and stakeholder fit, and document the right next steps for model training.

As a contractor, you will work asynchronously on assigned batches, with at least 10 hours per week, primarily reviewing and scoring tasks using a structured rubric. Compensation is hourly and determined after interview.

Qualifications

• Direct working experience in ai data science domain specialist operations on real teams for AI Data Science Domain Expert assignments.
• Clear written reasoning that names the policy or workflow being applied.
• Reliable async availability for at least 10 hours per week.

Responsibilities

• Review AI outputs against current ai data science domain specialist operations workflows, playbooks, and firm policy for AI Data Science Domain Expert assignments.
• Grade tone, escalation logic, and stakeholder fit on a structured rubric.
• Flag operational risk, missed escalations, and policy-adherence gaps with severity tags.
• Capture the right next step so the modeling team can train on it.

Job description

AI Data Science Domain Expert is a remote review track for evaluating AI outputs across ai data science domain specialist operations workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.

Category: Enterprise Workflow & Tool Use - Pay: $85 / hr - Location: Remote - US-eligible - Contractor

AI Data Science Domain Expert is a remote review track for evaluating AI outputs across ai data science domain specialist operations workflows.

Role details

About the role

AI Data Science Domain Expert is a remote review track for evaluating AI outputs across ai data science domain specialist operations workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk; and document the right next step so the modeling team can train on it.
AI Data Science Domain specialist operations AI has to fit into an actual day at work. AuraOne uses experienced operators to grade outputs the way a senior peer would - checking workflow, policy, and the unwritten rules that decide whether a task actually gets done.
Judge tool-use tasks and enterprise agent behavior. Operational judgment is the skill.

Responsibilities

• Review AI outputs against current ai data science domain specialist operations workflows, playbooks, and firm policy for AI Data Science Domain Expert assignments.
• Grade tone, escalation logic, and stakeholder fit on a structured rubric.
• Flag operational risk, missed escalations, and policy-adherence gaps with severity tags.
• Capture the right next step so the modeling team can train on it.Track Operations & business review Work model Remote - Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Direct working experience in ai data science domain specialist operations on real teams for AI Data Science Domain Expert work.
• Comfort applying multi-page rubrics consistently across long batches.
• Clear written reasoning that names the policy or workflow being applied.
• Strong attention to detail and the ability to flag when a prompt itself is the problem.
• Reliable async availability for at least 10 hours per week.

Example tasks

• Grade a model's response to a real ai data science domain specialist operations ticket and rate workflow, tone, and escalation.
• Flag a missed escalation with the right severity tag and corrected next step.
• Adjudicate a disputed playbook call between two reviewers using firm guidance.
• Audit a 25-row batch for rubric consistency and report drift to the program lead.

Useful experience

• Prior experience training, calibrating, or QA-ing operations teams.
• Familiarity with AI-assisted workflow tooling and its failure modes.
• Bilingual experience for cross-region operations.

Compensation and schedule

Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Operational review
• Policy adherence
• Workflow judgment
• Stakeholder communication
• AI Data Science Domain specialist operations
• AI model evaluation

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.
• Placement timing depends on program demand and reviewer confirmation.