skills. Experience delivering complex projects and mentoring others. Desirable Postgraduate qualification (MSc/PhD) in data science, ML, or related subject. Experience with health data standards (HL7, FHIR, SNOMED). Familiarity with NHS datasets and national initiatives. Experience with BI tools such as Power BI, Tableau, or Looker. Research track record with academic or industry partners. Analytical & Judgement More ❯
as Docker and EKS/Kubernetes. Familiarity with one or more RnD research process and associated regulatory requirements. Exposure to healthcare data standards (CDISC, HL7, FHIR, SNOMEDCT, OMOP, DICOM). Exposure to big data technologies and handling. Knowledge of machine learning operations (MLOps) and model deployment. Strong problem-solving and analytical abilities. Excellent communication skills for More ❯
experience of working in a data analysis, business intelligence, or performance role within a healthcare or public sector environment. Strong understanding of NHS data sets, coding structures (e.g., SNOMED, ICD-10), and data flows across primary, community, and secondary care. Demonstrable experience in extracting, cleansing, and analysing complex datasets. Experience of producing reports and dashboards for senior managers More ❯
support evidence-based decision-making. Utilise Ardens Manager, EMIS, SystmOne, and Connected Care for accurate reporting and data extraction. Audit and maintain data quality, ensuring consistent use of SNOMED codes and clinical templates. Provide the PCN Board with high-quality performance reports, insights, and recommendations. Digital Transformation & Support Support practices to optimise clinical systems (EMIS, SystmOne, AccuRx, Connected More ❯
non-negotiable) Experience delivering end-to-end observational studies using real-world datasets Proficient in study design, regulatory writing (protocols, SAPs, TFLs, CSRs) Knowledge of coding systems (ICD, SNOMED, GPI, HCPCS) and RWD sources (claims, EHR, registries) Familiar with regulatory trends around pragmatic trials, external control arms, and synthetic cohorts Skilled in handling and cleaning messy, multimodal data More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Cubiq Recruitment
non-negotiable) Experience delivering end-to-end observational studies using real-world datasets Proficient in study design, regulatory writing (protocols, SAPs, TFLs, CSRs) Knowledge of coding systems (ICD, SNOMED, GPI, HCPCS) and RWD sources (claims, EHR, registries) Familiar with regulatory trends around pragmatic trials, external control arms, and synthetic cohorts Skilled in handling and cleaning messy, multimodal data More ❯
