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Medical/clinical coding specialists (snomed) required for ai project

Newcastle
Posted: 17 November
Offer description

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.

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