Job Description
We are seeking a highly skilled Senior Clinical Data Manager to join our elite Clinical Operations team. Meridian Therapeutics is pioneering next-generation therapies, and you will play a critical role in ensuring the integrity and reliability of our clinical data across global trials.
In this senior-level position, you will lead data management initiatives, define data standards, and mentor junior staff. You will work closely with cross-functional stakeholdersâincluding Biostatisticians, Clinical Operations, and Regulatory Affairsâto ensure our data supports successful regulatory submissions and publication-quality analysis.
Why Join Us?
- Work on cutting-edge therapeutic areas including oncology and rare diseases.
- Competitive compensation package and comprehensive benefits.
- Opportunity for leadership growth within a collaborative environment.
Responsibilities
- Lead the end-to-end clinical data management lifecycle, from data capture to database lock, ensuring high-quality deliverables.
- Define and enforce data standards, ensuring strict adherence to CDISC (SDTM/ADaM) guidelines and internal Standard Operating Procedures (SOPs).
- Perform complex data cleaning, validation, and reconciliation to resolve discrepancies with study teams and sponsor representatives.
- Collaborate with Biostatisticians and Data Scientists to design validation rules and troubleshoot data issues to optimize data flows.
- Ensure full compliance with Good Clinical Practice (GCP), 21 CFR Part 11, and relevant regional regulations (FDA, EMA).
- Conduct data quality reviews and implement quality improvement initiatives.
Qualifications
- Bachelorâs or Masterâs degree in Life Sciences, Biostatistics, Computer Science, or a related field.
- Minimum of 5 years of progressive experience in Clinical Data Management within the pharmaceutical or biotechnology industry.
- Expertise in CDISC standards (SDTM, ADaM) and working knowledge of database development tools (e.g., Rave, Oracle Clinical, Central Medidata, or Rww).
- Proficiency in programming languages such as SAS, R, or Python for data manipulation, validation, and automation.
- Strong understanding of data governance, data quality metrics, and regulatory requirements.
- Excellent communication skills with the ability to present technical findings to non-technical audiences.