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Medical/Clinical Coding Specialists (SNOMED/ICD) Required for AI Project at Mentis AI. Remote Location: Global. 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.