Medical/Clinical Coding Specialists (SNOMED) Required for AI Project

We are seeking medical or clinical coders to assist in coding medical questionnaires to SNOMED codes on a dedicated labeling platform.

You will work asynchronously to code the de-identified data from patient questionnaires, helping train and refine AI models for automated clinical coding.

Key Responsibilities:

• Questionnaire Coding & Mapping: Map each patient questionnaire item (5-15+ per questionnaire) to SNOMED codes, including medications, conditions, allergies, reactions, side effects, and severity indicators.
• Quality Assurance & Data Structuring: Ensure consistent and accurate application of medical codes following provided guidelines and project standards.
• FHIR Data Integration: Support mapping of coded data to FHIR-compliant structures (training and guidance provided).
• Platform-Based Labeling: Use a dedicated labeling platform to review, code, and validate data efficiently.
• Feedback & Collaboration: Provide feedback to improve coding guidelines, identify ambiguities in source data, and improve AI-assisted mappings.

Qualifications:

• Medical coding experience: Minimum 1 year of professional experience in medical coding.
• Coding knowledge: Demonstrated experience in SNOMED coding; if not, a strong grasp of standard medical coding systems (ICD, CPT, LOINC, etc.) and principles is required.
• Attention to detail: Proven track record of accuracy and consistency in clinical data coding.
• Technical proficiency: Comfortable using structured data labeling tools and digital platforms.
• Language: Professional working English proficiency for written deliverables.

Legal Status:

You will have the right to work in your country of residence.
You will work as an independent contractor.

Why Join Us?

• Flexible Work Arrangements: Short-term, fully remote project (estimated duration 1-2 months).
• Competitive Compensation: Hourly rate paid out weekly
• Collaborative Environment: Be part of a multidisciplinary initiative advancing automation in clinical coding.