Medical Oncologist Clinical Documentation Reviewer

OpenTrain AI, Inc.

United States

Remote

USD 220,000 - 248,000

Part time

3 days ago
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Job summary

OpenTrain AI, Inc. is seeking a Medical Oncologist Clinical Documentation Reviewer for a remote, part-time contractor role.

You will evaluate AI-generated transcripts and notes from outpatient oncology visits for accuracy, completeness, and clinical clarity, ensuring they support quality patient care. The ideal candidate has an MD or DO with board certification or eligibility in Medical Oncology, plus at least two years of outpatient oncology experience, and strong written communication to

Qualifications

  • MD, DO, or an equivalent medical degree.
  • Board certification or eligibility in Medical Oncology.
  • At least two years of outpatient medical oncology experience after fellowship.
  • Experience reviewing AI-generated clinical documentation and ensuring accuracy.

Responsibilities

  • Review AI-generated transcripts and notes from outpatient oncology visits.
  • Assess accuracy, completeness, and clinical clarity of documentation.
  • Provide actionable feedback to improve AI note generation and EHR templates.
  • Identify missing or incorrect cancer diagnoses, staging, treatments, and lab results.

Skills

Attention to detail
Strong written communication
Outpatient oncology experience

Education

MD/DO or equivalent medical degree

Tools

Electronic Health Records (EHR) systems
AI scribe familiarity

Job description

Medical Oncologist Clinical Documentation Reviewer

Review AI-generated outpatient oncology transcripts and notes for accuracy, completeness, and clinical clarity. This remote, part-time contractor role pays $160 to $180 per hour.

Remote Hourly · $160–$180/hr

$160–$180/hr

Contract, part-time

Remote

United States

The work

You will review AI-generated transcripts and clinical notes from outpatient oncology visits. Your feedback will help improve documentation of diagnoses, treatment decisions, clinical findings, and ongoing patient care.

  • Check History of Present Illness, interval histories, and Assessment and Plans for accuracy and completeness.
  • Identify missing or incorrect details about cancer diagnoses, staging, treatments, laboratory results, and imaging findings.
  • Review documentation of chemotherapy, immunotherapy, targeted therapies, supportive care, treatment response, toxicities, disease progression, and follow-up care.
  • Provide clear, practical feedback that improves AI-generated notes and electronic health record documentation.
What it pays and takes

This is a part-time, project-based remote contractor role for professionals based in the United States. The work requires medical oncology expertise and strong attention to clinical detail.

  • Pay: $160 to $180 per hour.
  • Location: Remote and open to candidates based in the United States.
  • Education: MD, DO, or an equivalent medical degree.
  • Certification: Board certification or eligibility in Medical Oncology.
  • Experience: At least two years of recent outpatient medical oncology experience after fellowship.
  • Clinical knowledge: Strong experience diagnosing and managing solid tumors, systemic cancer therapies, treatment-related toxicities, supportive care, and laboratory and imaging interpretation.
  • Documentation skills: Ability to write and assess History of Present Illness, interval histories, and Assessment and Plans.
  • Communication: Strong written communication and close attention to clinical detail.
  • Helpful background: Experience with a broad range of solid tumors, complex oncology cases, AI scribe technology, electronic health record templates, medical chart review, or clinical annotation.
About AI training work

AI training work uses human review to help improve artificial intelligence systems. In this role, your medical oncology experience helps assess whether AI-generated clinical documentation is accurate, complete, and useful for real clinical work. OpenTrain is where people find these projects and apply to build experience in the field.

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