Director, Translational Data Enablement

In this role, you will lead the transformation of translational and biomarker data into reusable, FAIR data products that accelerate drug discovery and development. You will sit at the crossroads of science, technology, and data leadership to deliver high-quality, scalable data assets and end-to-end data flows. You’ll manage a 12–15 person distributed team and drive enterprise-wide data coherence and strategy. The opportunity centers on building AI-ready platforms that enable cross-functional impact and evidence-based decision making.

• in-office collaboration three days per week
• flexible work options
• lead global, cross-functional team
• opportunity to shape translational data standards
• industry-facing speaking and network opportunities

• Own the delivery of analysis-ready datasets for precision medicine, biomarker discovery, and hypothesis validation
• Define FAIR-compliant data standards for translational/biomarker data (omics, imaging, proteomics)
• Create data catalogs, metadata standards, and usage guidelines with feedback loops for improvement
• Build semantic schemas and harmonization layers to integrate data from diverse sources
• Specify technical requirements for translational data workflows (ingestion, validation, APIs)
• Lead automation projects to reduce manual curation and measure efficiency gains
• Ensure integration with enterprise systems (clinical data lakes, AI/ML platforms)
• Pilot new technologies (agentic AI, ML-driven quality assurance) at scale
• Recruit, mentor, and scale a 12–15 person distributed team of data stewards and engineers
• Define multi-year roadmap for expanding data standardization across therapeutic areas and partners
• Drive proactive data generation shifts (Shift Left) and present at industry forums

• PhD or Master degree in bioinformatics, biomedical data science, molecular medicine, or related field
• 5+ years of experience with publications or thought leadership on biomarker standardization and data delivery
• Experience leading cross-functional, global teams with budget oversight
• Familiarity with FAIR data principles, semantic interoperability, or data standards in research contexts (GA4GH, MIAME)
• Track record of scaling data governance or data stewardship programs across multiple labs or studies
• Familiarity with agentic AI, machine learning, or LLM-driven automation in data/workflows
• Experience with biomarker platform companies or research consortia (e.g., NCI SEQC, GTEx)

• collaborative mindset
• strong strategic and communication skills
• leadership and mentoring ability
• FAIR data principles
• data standards and semantic interoperability
• data catalogs and metadata management