relationrx - Director/Senior Director, Data Strategy
Requirements
• A graduate degree in Bioinformatics, Computer Science, Computational Biology, or a related field (PhD preferred). • Demonstrated success in leading data strategy, including planning and execution in a matrix environment • Extensive experience with data strategy, management and acquisition in the life sciences, preferably including working with large biobanks and public databases. (7 years + experience) • Familiarity with data management, storage and processing tools and cloud-based data management platforms • Ideally, fluency in writing functioning code for a variety of tasks (such as data pipelines), including the skilled use of modern coding agents. Basic knowledge of computer science concepts sufficient to understand important concepts including latency, throughput, bottlenecks, race conditions etc. • Experience of acquisition, curation, and quality assurance efforts in research or drug discovery or a similar regulated setting • Deep understanding of various data types and ontologies, including -omics, imaging, and clinical data. • Proven experience with data governance frameworks and ensuring compliance with data protection regulations. • Ability to lead cross-functional initiatives and manage stakeholder relationships across a wide range of scientific and technical disciplines. • Experience working with machine learning teams and an understanding of data needs for model development. • Experience with large-scale data integration efforts, biobanks like UK Biobank, or databases such as dbGaP. • Knowledge of FAIR data principles and experience implementing data governance strategies in compliance with industry standards. • Personally, you are: • collaborative team player with a strong desire to drive impact. • an excellent communicator and are comfortable presenting complex data strategies to both technical and non-technical stakeholders. • detail-oriented, curious, and passionate about using data to drive scientific innovation. • Comfortable and thrive in fast-paced, dynamic environments • Driven by impact, motivated and curious • Humble and hungry to learn and have a strong sense of accountability • Passionate about making a difference in patients’ lives • WORKING STYLE & CULTURE AT RELATION • At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! • RECRUITMENT AGENCIES • Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. • Relation is a committed equal opportunities employer.
Responsibilities
• Data Strategy: Define and execute Relation’s data strategy in partnership with key stakeholders, ensuring that Relation’s data is a compounding asset that supports all aspects of drug discovery, research and development. • Data Management: Create and maintain data catalogues, define data standards and ontologies, and ensure proper metadata and data lineage tracking. • Data infrastructure: Work closely with the VP Engineering to guide the development of a robust data infrastructure in a rapidly scaling TechBio • Collaboration: Work closely with interdisciplinary teams, such as machine learning engineers, bioinformaticians, and scientists, to ensure data is ready for use in research and drug discovery. • Data Acquisition: Procure and integrate external datasets (e.g. UK Biobank, public databases) and manage data partnerships to enrich Relation's data ecosystem. • Governance: Implement data governance policies that ensure responsible, secure, and compliant data usage, aligning with evolving regulatory requirements. • Quality Assurance: Lead data curation efforts, ensuring the quality and integrity of data assets across multiple domains including omics, imaging, and clinical data. • Team Leadership: Build and manage a high-performing data strategy, governance and acquisition team, fostering a culture of excellence and continuous improvement.
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