Major accountabilities:

• Interface seamlessly with semantic experts across the company including the Biomedical Research (BR), Development (Clinical Operations & Analytics) and others.  Establish and implement the multimodal data roadmap for data42 contributing to identify novel drug targets and therapeutic strategies. 

• Apply all FAIR principles ensuring that all data assets are properly tagged, governed and aligned with business objectives and make any data understandable for data42 end users 

• Maintain data catalog of all data assets managed across the data42 ecosystem 

• Brings expertise and supports the implementation of the standardization of data models and reference data across all master data defined by each data assets owner. 

• Maintain AI-enabled metadata tools to facilitate data findability and metadata management across all data assets and expose them to data42 end users. 

• Lead and coordinate pipelines teams towards implementing data42’s vision for enabling disease-centric multimodal investigation.   

• Coordinate closely with teams working on semantics and metadata standards across Novartis.  

• In conjunction with a scrum master, run the team through an agile methodology 

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Experience/Professional requirements:

• Third level Degree qualification and 10+ years of professional experience in metadata management, semantic technologies, ontology, Artificial Intelligence (AI), and insights generation, within the pharmaceutical, biotechnology, or a related industry. 

• In-depth knowledge of industry standardization like CDISC (SDTM, ADaM, SEND), HL7 FHIR, MedDRA, and WHODrug. 

• Demonstrated experience in leading and implementing large-scale data projects and initiatives, particularly those involving semantic technologies, ontologies, and knowledge graphs. 

• Proficiency in FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and their application in a business/biomedical context. 

• In-depth knowledge of Ontological authoring & engineering e.g. ontology development process, ontology life cycle, methodologies, tools and languages required for building ontologies. 

• Knowledge of Generative AI and Large Language Models (LLM), with a focus on leveraging these technologies to transform unstructured and unharmonized data sources into insightful and actionable information.  

• Semantic Web Technologies (Web 2.0/3.0, RDF/OWL/SKOS, SPARQL...)  and their application to the biomedical domain (OBO). 

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve