Associate Director leading FAIR data operations in Oncology data science. Focusing on quality data products and team management in Life Sciences/Pharma.
Responsibilities
Lead the strategy and execution of FAIR (Findable, Accessible, Interoperable, Reusable) data operations across oncology biomarkers, translational science, clinical development, and real-world evidence
Own the operating model for end-to-end data flows to deliver scalable, compliant, high-quality data products
Partner with scientific, clinical, engineering, and governance leaders to embed FAIR-by-design and strengthen cross-functional data culture
Define the FAIR data roadmap, OKRs, and standards for ingestion, curation, harmonization, and provisioning across multi-omics, imaging, clinical, and RWE; drive enterprise metadata and ontology adoption
Build and develop a high-performing team; lead cross-functional squads and foster continuous improvement
Design and oversee primary data flows, monitoring, SLOs, incident/problem management, documentation, lineage, and catalog-driven access
Implement data/metadata standards and controlled vocabularies; embed privacy-by-design and regulatory compliance (e.g., GDPR)
Partner with data product teams to deliver reusable FAIR assets, accelerate curation, and capture metadata at source
Translate scientific needs into requirements, run governance cadences, communicate risk/value, and champion agile/ DataOps ways of working
Requirements
Master's degree in Data Science, Bioinformatics, Computational Biology, Life Sciences; PhD preferred
5+ years' experience in data management/operations within Life Sciences/Pharma R&D and 2+ years leading teams/programs
Proven scale-up of FAIR practices across complex R&D data (digital pathology, genomics, -omics, clinical, RWE)
Technical: Unix/Python familiarity, workflow orchestration, standards/ontology implementation, data privacy/compliance, and strong stakeholder communication
Benefits
qualified retirement programs
paid time off (i.e., vacation, holiday, and leaves)
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