Medical Doctor with SNOMED Coding Experience (UK)

Job description

We are seeking qualified medical doctors to annotate and code clinical documents with SNOMED CT, with a focus on accuracy and consistency against detailed coding guidelines. You will work asynchronously on a dedicated annotation platform, coding de-identified clinical notes and documentation including discharge summaries, lab results and progress notes against SNOMED CT concepts to support the development of clinical AI platforms. This is a remote, flexible and short-term project. ## **Key Responsibilities** - **Structured Annotation:** Identify clinically relevant concepts across discharge summaries, lab results and prognosis notes, and map them to the correct SNOMED CT codes on a dedicated platform. - **Guideline Application:** Work to a coding guideline covering hierarchy scope, negation, medication scope, section-level inclusions and compound coding, applied consistently across a large volume of documents. - **Edge Case Handling:** Flag ambiguous or contested cases with a short rationale so guidance can be refined. - **Quality Review:** Participate in adjudication rounds to resolve disagreements and reach a consensus code set. ## **Qualifications:** **License:** GMC Registered Doctor based in the UK **Experience:** Minimum 1–2 years of clinical practice, with SNOMED CT coding or clinical terminology experience. **Knowledge:** Strong grounding in clinical documentation, terminology and coding conventions. **Attention to detail:** Proven accuracy and consistency in coding or clinical review work. **Technical proficiency:** Comfortable using structured annotation tools and digital platforms. **Language:** Native or near-native written English. ## **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:** Part-time, remote and fully asynchronous. - **Competitive Compensation:** Hourly rate, paid weekly - **Professional Development:** Hands-on experience in clinical AI development and terminology work, shaping how AI systems interpret clinical records and assign medical codes.