
**Multimodal Data Architectural Specialist**
2 weeks ago
As a key member of our team, you will play a vital role in shaping the future of biomedical data management. The Semantic Technologies Lead will be responsible for establishing and implementing multimodal data roadmaps that contribute to identifying novel drug targets and therapeutic strategies.
- Interface seamlessly with semantic experts across various departments to establish and implement multimodal data roadmaps.
- Apply FAIR principles to ensure all data assets are properly tagged, governed, and aligned with business objectives.
- Maintain a comprehensive data catalog of all data assets managed within the ecosystem.
- Bring expertise to support the implementation of standardized data models and reference data across all master data defined by each data asset owner.
- Maintain AI-enabled metadata tools to facilitate data findability and metadata management across all data assets.
- Lead and coordinate pipeline teams towards implementing the company's vision for enabling disease-centric multimodal investigation.
The successful candidate will be measured on their ability to:
- Support the vision of releasing a disease-centric multimodal investigation across the RDC continuum.
- Deliver business value through cost savings, data rationalization, and storage costs reduction.
- Demonstrate improved speed to insights generation through semantics implementations.
The ideal candidate will have a profound impact on the organization by:
- Building a large, scalable, and integrated data platform redefining the role of data in building disease-centric assets and insights.
- Enabling multimodal and multidimensional data frameworks to represent, organize, and analyze complex biomedical data, enhancing R&D efficiency and innovation.
To succeed in this role, you must possess:
- A Master's degree or higher in Computer Science, Engineering, Ontology, Semantics, Artificial Intelligence, or a related field.
- Cross-cultural experience, people leadership, and project management skills.
- 10+ years of professional experience in metadata management, semantic technologies, ontology, AI, and insights generation within the pharmaceutical, biotechnology, or related industry.
- In-depth knowledge of industry standardization such as CDISC (SDTM, ADaM, SEND), HL7 FHIR, NCI, MedDRA, and WHODrug.
- Experience with regulated environments such as GDPR and/or GxP when working with products, tools, and medical & pharmaceutical data sources.
- Proficiency in FAIR data principles and their application in a business/biomedical context.
- Knowledge of ontological authoring & engineering, semantic web technologies, and generative AI.
- Clinical Data Management, Cross-Functional Team, Data Architecture, Data Governance, Data Management, Data Quality, Data Science, Data Strategy, Drug Development, Master Data, People Management, Waterfall Model
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