Medical Records Coder - Remote

Medical Records Coder - Remote

Location: Remote – United States
Employment Type: Independent Contractor
Compensation: $96,000–$134,400/year equivalent
Hourly Rate: $50–$70/hour

Annualized compensation is an illustrative equivalent based on 40 hours/week × 48 weeks/year. Actual earnings depend on hours worked, project availability, and approved work.

About the Role

We are seeking experienced Medical Records Coders with CCS, CIC, or CPC certification to review, interpret, and annotate clinical documentation for a healthcare AI training project.

You will apply your medical coding expertise to real-world patient records, ensuring accurate diagnosis and procedure code assignment across different healthcare settings. Your work will help improve how advanced AI systems interpret clinical documentation, apply coding guidelines, and identify relevant medical information.

No previous AI experience is required. Your coding expertise is what matters.

Key Responsibilities

• Review and annotate medical records, including encounter notes, progress notes, operative reports, consultations, laboratory and imaging results, and discharge summaries.

• Assign and validate ICD-10-CM, ICD-10-PCS, CPT, and HCPCS codes based on documented clinical information.

• Identify principal and secondary diagnoses and sequence codes according to official coding guidelines.

• Assign applicable modifiers and Present on Admission (POA) indicators.

• Apply coding conventions and payer-neutral best practices using the Official Guidelines for Coding and Reporting and AHA Coding Clinic guidance.

• Identify incomplete, conflicting, or ambiguous clinical documentation and flag opportunities for provider queries.

• Review coding annotations for accuracy, completeness, and consistency.

• Collaborate with project stakeholders to clarify requirements and resolve documentation questions.

• Provide actionable feedback on complex coding cases and guideline interpretation to improve AI model performance and project workflows.

Required Qualifications

• Active CCS (AHIMA), CIC (AAPC), or CPC (AAPC) certification.

• Strong working knowledge of ICD-10-CM, ICD-10-PCS, and CPT coding.

• Hands-on experience coding directly from medical records.

• Ability to interpret clinical documentation and accurately assign and sequence diagnosis and procedure codes.

• Understanding of the Official Guidelines for Coding and Reporting and AHA Coding Clinic guidance.

• Strong attention to detail and ability to identify documentation gaps and coding discrepancies.

• Excellent written and verbal communication skills.

• Access to current ICD-10-CM, ICD-10-PCS, and CPT code sets and official coding resources.

Preferred Experience

• Medical coding experience across multiple healthcare settings, including:

  • Acute care and inpatient facilities

  • Outpatient services

  • Emergency departments

  • Physician practices

• Experience reviewing complex clinical documentation and resolving challenging coding scenarios.

• Familiarity with medical record annotation, coding quality review, or data validation.

• Ability to communicate coding decisions and collaborate effectively with multidisciplinary stakeholders.

Core Skills

Medical Records Coding • ICD-10-CM • ICD-10-PCS • CPT • HCPCS • CCS • CIC • CPC • Clinical Documentation Review • Medical Record Annotation • Code Assignment and Sequencing • AHA Coding Clinic • Official Coding Guidelines • POA Indicators • Coding Modifiers • Documentation Queries • Data Quality Assurance

Why This Opportunity?

Use your professional coding knowledge to contribute to the development of advanced healthcare AI systems. Your expertise will help improve the accuracy of clinical data interpretation, strengthen medical coding quality, and teach AI models to apply established coding standards to real-world documentation.

If you are a certified medical coder with strong medical record review experience and a commitment to coding accuracy, this remote opportunity offers a way to apply your skills to the evolving field of healthcare AI.