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Data Modeller

Job in London, Greater London, W1B, England, UK
Listing for: CODEVERSE LIMITED
Full Time position
Listed on 2026-06-04
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, Data Science Manager, Data Security
Salary/Wage Range or Industry Benchmark: 75000 GBP Yearly GBP 75000.00 YEAR
Job Description & How to Apply Below
Senior Data Modeller

Role Overview :
We are seeking an expert Senior Data Modeller to lead our modelling strategy across complex biomedical and scientific domains. You will be responsible for translating ambiguous scientific requirements into robust canonical data models and driving schema review, approval, and publication processes. Key Details:
Experience Level: 10 years overall (with 4 years strong Data Modelling) Availability: 0-1 weeks (plus 1-2 week onboarding)

Location:

UK Mandatory Skills & Responsibilities:
Leadership & Strategy:
Lead modelling strategy across data harmonisation, pipeline validation, knowledge graph, and FAIR data product requirements. Requirements Translation:
Translate ambiguous scientific requirements into clear canonical data models. Ontology Management:
Make ontology reuse, extension, and mapping decisions (with documented rationale), and define persistent identifiers and consistent provenance fields. Risk Mitigation:
Identify modelling risks early, including metadata gaps, ontology conflicts, source data quality issues, lineage gaps, and downstream compatibility risks. Design & Architecture:
Design modular, reusable, and future-proof models aligned to FAIR principles (findability, accessibility, interoperability, reusability) and enterprise standards. Technical Implementation:
Apply practical experience with LinkML (or equivalent), including classes, slots, ranges, identifiers, constraints, and ontology bindings. Lifecycle Management:
Manage schema life cycles via Git Hub-based repositories, semantic versioning, tagged releases, and metadata catalogues. Stakeholder

Collaboration:

Partner with Scientific Knowledge Engineering, Causal Biology SMEs, Data Engineering, and Platform teams.
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