Senior Director, Clinical Data Management and Analytics
Iovance Biotherapeutics, Inc.
4 hours ago
Remote
United States
Clinical Research and Development
Responsibilities:
- Define and implement the overall vision, strategy, and goals for the clinical data management department.
- Lead, manage, and develop data management teams (resource planning, staff training, performance reviews).
- Ensure data integrity, quality, and compliance with regulatory requirements (e.g., FDA, ICH, GCPs) and internal SOPs.
- Generate novel insights from data and present them via rich and intuitive visualizations.
- Ensure quality of deliverables by applying analysis and reporting standards.
- Drive development and implementation of innovative strategies and technologies.
- Independently develop, troubleshoot, and maintain complex programs and utilities based on predefined specifications and existing standards.
- Provide technical guidance to external partners on project/data standards and analysis practices.
- Identify opportunities for increased efficiency and consistency; provide SME support for continuous improvement.
- Build partnerships and collaborate cross-functionally to support development, regulatory approval, and market acceptance.
Qualifications / Required:
- Extensive experience in clinical data management and systems; proven leadership in oncology.
- Proficiency with EDC systems (e.g., Medidata Rave), CDISC standards, and clinical trial processes.
- Experience with global trials and regulatory submissions (FDA, EMA).
- MS/BS/BA (or suitable relevant qualification).
- 13+ years of direct experience in clinical data management in biotechnology or pharmaceutical industry.
Skills / Required:
- Demonstrated ability to lead, motivate, and develop teams.
- Excellent communication and interpersonal skills; ability to explain complex technical information to non-technical audiences.
- Strong problem-solving and decision-making.
- Ability to work in a fast-paced environment with multiple simultaneous projects.
- Ability to work within budget constraints and use resources efficiently.
Preferred:
- Experience with AI applications in data management.
Application instructions:
- Not provided.
- Define and implement the overall vision, strategy, and goals for the clinical data management department.
- Lead, manage, and develop data management teams (resource planning, staff training, performance reviews).
- Ensure data integrity, quality, and compliance with regulatory requirements (e.g., FDA, ICH, GCPs) and internal SOPs.
- Generate novel insights from data and present them via rich and intuitive visualizations.
- Ensure quality of deliverables by applying analysis and reporting standards.
- Drive development and implementation of innovative strategies and technologies.
- Independently develop, troubleshoot, and maintain complex programs and utilities based on predefined specifications and existing standards.
- Provide technical guidance to external partners on project/data standards and analysis practices.
- Identify opportunities for increased efficiency and consistency; provide SME support for continuous improvement.
- Build partnerships and collaborate cross-functionally to support development, regulatory approval, and market acceptance.
Qualifications / Required:
- Extensive experience in clinical data management and systems; proven leadership in oncology.
- Proficiency with EDC systems (e.g., Medidata Rave), CDISC standards, and clinical trial processes.
- Experience with global trials and regulatory submissions (FDA, EMA).
- MS/BS/BA (or suitable relevant qualification).
- 13+ years of direct experience in clinical data management in biotechnology or pharmaceutical industry.
Skills / Required:
- Demonstrated ability to lead, motivate, and develop teams.
- Excellent communication and interpersonal skills; ability to explain complex technical information to non-technical audiences.
- Strong problem-solving and decision-making.
- Ability to work in a fast-paced environment with multiple simultaneous projects.
- Ability to work within budget constraints and use resources efficiently.
Preferred:
- Experience with AI applications in data management.
Application instructions:
- Not provided.