About the Role
This role leads the planning, execution, and oversight of clinical data management activities for complex trials, ensuring high-quality data collection, validation, and delivery to support regulatory submissions and analysis.
Responsibilities
- Lead end-to-end data management processes for clinical studies
- Develop and maintain data management plans and timelines
- Oversee database design and validation activities
- Ensure adherence to regulatory standards and data quality protocols
- Collaborate with cross-functional teams including biostatistics and clinical operations
- Manage data cleaning and query resolution workflows
- Review and approve data validation specifications
- Support data transfer and integration from external sources
- Lead vendor oversight for data management deliverables
- Conduct data review and reconciliation activities
- Ensure compliance with SOPs, GCP, and applicable regulations
- Prepare data for database lock and archiving
- Participate in study risk assessments and data management strategy sessions
- Mentor junior data management staff
- Contribute to the development of data standards and best practices
- Support audit and inspection readiness efforts
- Review and approve data management documentation
- Coordinate with medical coding teams for terminology standardization
- Oversee electronic data capture system configuration
- Ensure data traceability and audit trail integrity
- Facilitate cross-study data consistency
- Participate in system and process improvement initiatives
- Manage timelines and deliverables for data management milestones
- Serve as primary contact for data management issues
- Support regulatory submission data requirements
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with partial remote flexibility
Team
Collaborative team within clinical research and data sciences
Why Join Us
- Opportunity to work on cutting-edge clinical research in high-impact therapeutic areas
- Supportive culture that values innovation, collaboration, and professional growth
Technology and Tools
- Access to modern data management platforms and analytics systems
- Use of industry-standard EDC, coding, and data integration tools
Not specified
