Data Information Model Developer

Join GSK as a Data Information Model Developer and help turn complex biomedical data into models that scientists and AI agents can use with confidence. You will design disease data information models for priority discovery areas, write the mapping rules that bring harmonized data them, and build the quality checks that keep them trustworthy. This is a hands-on role: you will work in code and modelling tools every day, use AI assistants to work faster, and partner with research, ontology and data platform teams as well as external partners. Responsibilities Design, develop, and maintain data information models and frameworks that support research and innovation. Work closely with cross-functional teams to understand their data needs and translate them into clear, reusable data structures. Document data definitions, relationships, and lineage to ensure clarity and usability for people as well as enabling context for AI agents to interpret the data correctly. Implement processes to ensure data quality, consistency, and compliance. Collaborate with engineering teams to integrate models into data platforms and pipelines. Support continuous improvement by reviewing and refining data modelling practices. Work with research scientists, data stewards and data platform teams to agree models and get them adopted. Basic Qualification Degree in Computer Science, Data Science, Information Management, or a related field. Proven experience in data modelling, designing information architectures, or similar roles in pharma setting. Proven experience curating, harmonizing or integrating biomedical, pharmaceutical or healthcare data. Proven experience using AI assistants or generative AI tools in daily work, with a critical eye on their output. Strong skills in data analysis and the ability to translate complex requirements into clear models. Familiarity with database technologies and data integration concepts. Ability to write clear documentation and communicate with technical and non-technical colleagues. Working knowledge of biomedical ontologies and standards such as NClt, MONDO, EFO, GO, ChEBI, CDISC Preferred Qualification Understanding of data governance, privacy, and security best practices. Familiarity with programming or scripting languages like SQL, Python, or others used in data workflows. Experience preparing data for AI agents. Contributions to standards or ontology communities (e.g. CDISC, FHIR, OBO Foundry, Pistoia Alliance). Job Data by YubHub .