Remote Life Sciences AI Review & QA Expert (Python)

AuraOne, Inc.; United States; Remote; USD 34,000 - 62,000; Full time

Job summary

AuraOne, Inc. is seeking a Life Sciences Research Expert (Python) for a remote contractor role eligible in the United States.

You will review AI outputs within life sciences operations, evaluate workflow correctness, policy adherence, and stakeholder fit, and flag risks to guide modeling team training. Work asynchronously for at least 10 hours per week, using a multi-page rubric and providing clear reasoning that cites the applicable policy or workflow.

Qualifications

• Direct working experience in life sciences research specialist operations on real teams for Life Sciences Research Expert (Python) 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.

Responsibilities

• Review AI outputs against current life sciences research specialist operations workflows, playbooks, and firm policy for Life Sciences Research Expert (Python) 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.
• Adjudicate disputed treatments against published playbooks or firm guidance.
• Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

Life Sciences Research specialist ops

Software engineering

Job description

AuraOne, Inc. is seeking a Life Sciences Research Expert (Python) for a remote contractor role eligible in the United States.

You will review AI outputs within life sciences operations, evaluate workflow correctness, policy adherence, and stakeholder fit, and flag risks to guide modeling team training. Work asynchronously for at least 10 hours per week, using a multi-page rubric and providing clear reasoning that cites the applicable policy or workflow.