Clinical Data Manager

We are seeking an experienced and detail-oriented Clinical Data Manager to join our growing clinical operations team. This role is critical in ensuring the integrity, accuracy, and quality of clinical trial data, with a particular focus on studies in rare and orphan diseases. You will work cross-functionally with clinical, biostatistics, regulatory, and external vendors to manage data across all phases of clinical development.

Key Responsibilities

• Lead and manage end-to-end data management activities for assigned clinical trials, from study start-up through database lock.
• Develop and review data management plans (DMPs), case report forms (CRFs), edit check specifications, and data validation rules.
• Oversee data cleaning activities, including query generation and resolution, discrepancy management, and data reconciliation.
• Collaborate with CROs and external vendors to ensure timely and high-quality data deliverables.
• Ensure compliance with regulatory requirements (e.g., ICH-GCP, CDISC standards) and internal SOPs.
• Participate in protocol review, CRF design, and database build processes.
• Support audits and inspections by regulatory authorities.
• Provide input into the development of rare disease-specific data strategies, including patient-reported outcomes and real-world data integration.
• Contribute to continuous improvement initiatives within the data management function.

Qualifications and Experience

• Bachelor's degree in life sciences, health informatics, or a related field (Master's preferred).
• Minimum of 3-5 years of experience in clinical data management, with at least 1-2 years in rare disease or orphan drug trials.
• Strong understanding of clinical trial processes, data standards (CDISC, SDTM), and regulatory requirements.
• Proficiency with EDC systems (e.g., Medidata Rave, Oracle InForm, Veeva Vault).
• Experience working with CROs and external vendors.
• Excellent organizational, communication, and problem-solving skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Skills

• Experience with decentralized trials or real-world evidence (RWE) data.
• Familiarity with biomarker or genetic data integration.
• Knowledge of statistical programming languages (e.g., SAS, R) is a plus.