Description
Summary
Responsible for defining, implementing, and maintaining data standards and governance frameworks across research and laboratory environments. This role ensures high-quality, interoperable, and FAIR (Findable, Accessible, Interoperable, Reusable) data to support scientific discovery, digital innovation, and regulatory readiness. This role has accountability across the R&D and the Technical Operations teams to ensure that data enables the R&D Submission and the Technology Transfer cycle time and milestone targets. In addition, this role has accountability for working with the Search team to identify opportunities and obstacles in external collaborations and acquisitions.
Main Responsibilities & Accountabilities
Develop and maintain data standards for research and lab-generated data, such as assay data, instrument outputs, and metadata, ensuring consistency across platforms and teams
Establish governance frameworks to ensure consistent data capture, annotation, and integration across digital systems (e.g., ELNs, LIMS, data lakes)
Collaborate with scientists, lab managers, IT, and data stewards to embed data standards into lab workflows and digital systems, supporting seamless data integration and usage
Monitor compliance with established data standards, identifying opportunities for improvement and driving continuous quality enhancements
Represent the organization in external data standards bodies and consortia (e.g., Allotrope, FAIR sharing, Pistoia Alliance) to ensure alignment with global data standards and best practices
Support data quality, lineage, and traceability efforts, enabling the use of data for advanced analytics, AI/ML applications, and regulatory submissions
Provide training, guidance, and support to internal teams on data standards, ontologies, and governance best practices to ensure consistent adoption across the organization
Qualifications & Experience Requirements
1. Bachelor’s or Master’s degree in Life Sciences, Bioinformatics, Data Science, or a related field
2. 12+ years of experience in research data management, lab informatics, or data governance
3. Must have experience working within Research and Life sciences
4. Strong knowledge of scientific data standards (e.g., Allotrope, AnIML, ISA-Tab), ontologies (e.g., OBI, ChEBI), and metadata frameworks
5. Must have sound experience working within a AI digital strategy team setting
6. Experience with lab systems (e.g., ELN, LIMS, CDS) and data integration platforms
7. Excellent communication, stakeholder engagement, and documentation skills, with the ability to influence and guide teams on data governance best practices
About CSL Behring
CSL Behring is a global biotherapeutics leader driven by our promise to save lives. Focused on serving patients’ needs by using the latest technologies, we discover, develop and deliver innovative therapies for people living with conditions in the immunology, hematology, cardiovascular and metabolic, respiratory, and transplant therapeutic areas. We use three strategic scientific platforms of plasma fractionation, recombinant protein technology, and cell and gene therapy to support continued innovation and continually refine ways in which products can address unmet medical needs and help patients lead full lives.
CSL Behring operates one of the world’s largest plasma collection networks, CSL Plasma. Our parent company, CSL, headquartered in Melbourne, Australia, employs 32,000 people, and delivers its lifesaving therapies to people in more than 100 countries.
To learn more about CSL, CSL Behring, CSL Seqirus and CSL Vifor visit and CSL Plasma at .
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