Define the FAIR data roadmap, OKRs, and pragmatic standards for ingesting, curating, harmonizing, and provisioning molecular and imaging clinical data; drive enterprise metadata, ontology, and catalog adoption to enable findability and reuse
Serve as accountable data steward for genomic, proteomic, and other -omics readouts from clinical trials and for digital pathology/imaging modalities (e.g., WSI, radiology DICOM); ensure modality-specific QC, metadata capture, and traceability from site/vendor to analysis environment
Lead the design and implementation of data specifications, data transfer agreements (DTAs), and SLAs with CROs, central labs, biomarker assay providers, and imaging vendors; standardize templates and acceptance criteria; oversee onboarding and performance monitoring
Implement data/metadata standards and controlled vocabularies across modalities; embed privacy-by-design and regulatory compliance (e.g., GDPR) and align with clinical data standards and internal governance cadences
Drive delivery across cross-functional matrix teams of data SMEs, data engineers, alliance/partnership managers, clinical operations, translational biomarker leads, imaging scientists, biostatistics, quality/compliance, privacy/legal, procurement/vendor management, and IT/security
Orchestrate work plans, dependencies, and acceptance criteria; champion agile/DataOps practices to ensure timely, compliant, and reusable outputs without direct line management responsibilities
Translate scientific and operational needs into clear requirements and delivery plans; communicate risk, value, and trade-offs; drive adoption of standards and tools through training and change management

Requirements

Master's degree in Data Science, Bioinformatics, Computational Biology, Life Sciences or related; PhD preferred
5+ years' experience in data management/operations within Life Sciences/Pharma R&D
Demonstrated stewardship of clinical molecular data (e.g., NGS, qPCR, proteomics) and imaging/digital pathology or radiology data within clinical trials, including QC pipelines, metadata capture, and compliance controls
Proven track record implementing and scaling FAIR practices across complex R&D data (digital pathology, genomics/-omics, clinical) with measurable impact on data findability, interoperability, and reuse
Hands-on experience defining data specs, mapping guides, transfer protocols, and DTAs; managing external partners and ensuring timely, quality-compliant data deliveries
Proficiency with Unix and Python, workflow orchestration (e.g., Airflow, Prefect), data modeling and standards/ontology implementation, data privacy/compliance, and strong stakeholder communication and documentation skills.

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

data managementdata operationsdata specificationsmetadata standardsdata transfer agreementsquality control pipelinesdata modelingdata privacy compliancegenomic data stewardshipimaging data stewardship

Soft Skills

stakeholder communicationchange managementrisk assessmentvalue communicationtrade-off analysiscross-functional collaborationleadershiporganizational skillsagile practicesproblem-solving

Certifications

Master's degree in Data ScienceMaster's degree in BioinformaticsMaster's degree in Computational BiologyMaster's degree in Life SciencesPhD in related field