Lead, manage and develop a group of data standards experts to develop, implement and maintain end-to-end data standards from data collection to regulatory submission, including governing change control, publication, and communication of new/updated standards.
Responsibilities:
- Ensure compliance with applicable Corporate and Divisional policies/procedures
- Maintain in-depth knowledge of CDISC guidance/implementation guides and FDA electronic submission requirements; track trends in data mapping, standards compliance, metadata management, and data warehousing
- Review eCRF designs for CDASH/SDTM conformance and proactively correct issues
- Review SDTM conformance mapping specifications; provide CDISC expertise for source-to-SDTM mapping cross-functionally
- Execute and interpret results from CDISC validation tools (SDTM/define.xml, ADaM/define.xml); collaborate to resolve issues and document unresolved items
- Manage CDISC metadata/terminology libraries in a metadata repository; provide governance oversight to ensure metadata consistency
- Assist with development of data standards policies/procedures
- Communicate data standards concepts and regulatory guidance; represent the Data Standards group in cross-functional initiatives
- Train/mentor team members; support onboarding of new data standards analysts
- Support CDISC public review activities and submit at least one abstract per year to a CDISC Interchange
Qualifications (Minimum):
- B.S.; 12+ years relevant clinical research experience (or 10+ with a Masters)
- Expert knowledge in 3+ clinical data standards areas (e.g., CDASH, SDTM, ADaM, define.xml, controlled terminology, metadata management)
- Familiarity with BRIDG, ODM, SHARE
- Experience mapping/converting legacy data into SDTM domains for eCTD (minimum two successful CDISC-compliant submissions)
- Knowledge of international regulations for clinical data standards and regulatory dataset preparation
- Experience with metadata repository technology and data standards governance
- Experience managing metadata to support efficient system/process use