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Freelance Clinical Data Manager (m/f/d)
On behalf of a renowned client in the life sciences industry, we are seeking freelance support in clinical data management. The main task is to take responsibility for coordinating all data management activities in clinical trials.
- Typical responsibilities in this role:**
- Creation and review of the Data Management Plan (DMP) and the Data Validation Plan (DVP).
- Designing and implementing electronic case report forms (eCRFs) in EDC systems (Electronic Data Capture).
- Coordinating data collection, validation, and cleaning across the entire study lifecycle.
- Developing and conducting query processes to resolve data inconsistencies with study sites.
- Medical coding of adverse events (AEs) and medications (e.g., using MedDRA, WHODrug).
- Performing SAE reconciliation (matching serious adverse events).
- Preparing and executing the database lock after data collection is complete.
- Generating status reports and communicating with the study team (project management, monitoring, biostatistics).
- Relevant technologies, tools, or methods:**
- EDC systems: Medidata Rave, Oracle Clinical, Viedoc, Zelta, OpenClinica.
- Programming languages/analysis tools: SAS, R, Python, SQL.
- Standards: CDISC (SDTM, ADaM), GCP (Good Clinical Practice), 21 CFR Part 11.
- Collaboration tools: MS Teams, Jira, Confluence.
- Data visualization: Tableau, Power BI.
- Typical KPIs or success metrics:**
- Data quality: Query rate (number of queries per 1000 data points) < X; data entry error rate < 1%.
- Time management: Time from last patient last visit (LPLV) to database lock (target: 4–6 weeks).
- Efficiency: Average time to resolve queries (target: < 10 working days for critical queries).
- Compliance: 100% adherence to the milestones and processes defined in the DMP.
- Protocol adherence: Rate of protocol deviations related to data management < 5%.
- Specific challenges, risks, or considerations:**
- Managing increasing data volumes and sources (e.g., wearables, ePROs).
- Ensuring data integrity and security (cybersecurity, data protection/GDPR).
- Complexity from mid-study changes (protocol amendments) and their impact on the database.
- Maintaining consistent data quality across multiple global sites.
- Shortage of qualified professionals and high demands for training on study-specific systems.
- Concrete deliverables:**
- Finalized and approved Data Management Plan (DMP).
- Live and validated study database (EDC system).
- Regular data cleaning reports and status updates.
- Clean, quality-assured data ready for statistical analysis.
- Final locked study database with complete audit trail.
- Archived project documentation after study completion.
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Freelance Clinical Data Manager (m/f/d)
Industries
Biotechnology
Pharmaceutical
Areas
Quality Assurance (QA)
Research and Development (R&D)
Project info
- Period11.08.2025 - 11.11.2025
- Capacityfrom 90%
- Daily rate620 - 830€
- LocationMunich, Germany
- Language
- German(Native)
- German
- Remotefrom 80%
Description
On behalf of a renowned client in the life sciences industry, we are seeking freelance support in clinical data management. The main task is to take responsibility for coordinating all data management activities in clinical trials.
Typical responsibilities in this role:**
Creation and review of the Data Management Plan (DMP) and the Data Validation Plan (DVP).
Designing and implementing electronic case report forms (eCRFs) in EDC systems (Electronic Data Capture).
Coordinating data collection, validation, and cleaning across the entire study lifecycle.
Developing and conducting query processes to resolve data inconsistencies with study sites.
Medical coding of adverse events (AEs) and medications (e.g., using MedDRA, WHODrug).
Performing SAE reconciliation (matching serious adverse events).
Preparing and executing the database lock after data collection is complete.
Generating status reports and communicating with the study team (project management, monitoring, biostatistics).
Relevant technologies, tools, or methods:**
EDC systems: Medidata Rave, Oracle Clinical, Viedoc, Zelta, OpenClinica.
Programming languages/analysis tools: SAS, R, Python, SQL.
Standards: CDISC (SDTM, ADaM), GCP (Good Clinical Practice), 21 CFR Part 11.
Collaboration tools: MS Teams, Jira, Confluence.
Data visualization: Tableau, Power BI.
Typical KPIs or success metrics:**
Data quality: Query rate (number of queries per 1000 data points) < X; data entry error rate < 1%.
Time management: Time from last patient last visit (LPLV) to database lock (target: 4–6 weeks).
Efficiency: Average time to resolve queries (target: < 10 working days for critical queries).
Compliance: 100% adherence to the milestones and processes defined in the DMP.
Protocol adherence: Rate of protocol deviations related to data management < 5%.
Specific challenges, risks, or considerations:**
Managing increasing data volumes and sources (e.g., wearables, ePROs).
Ensuring data integrity and security (cybersecurity, data protection/GDPR).
Complexity from mid-study changes (protocol amendments) and their impact on the database.
Maintaining consistent data quality across multiple global sites.
Shortage of qualified professionals and high demands for training on study-specific systems.
Concrete deliverables:**
Finalized and approved Data Management Plan (DMP).
Live and validated study database (EDC system).
Regular data cleaning reports and status updates.
Clean, quality-assured data ready for statistical analysis.
Final locked study database with complete audit trail.
Archived project documentation after study completion.
Requirements
Must-haves:**
A degree in life sciences, (bio)informatics, statistics, or a comparable qualification.
Several years of practical experience in clinical data management in the pharmaceutical industry or at a CRO.
Solid knowledge of regulatory requirements (ICH-GCP, 21 CFR Part 11) and industry standards (CDISC).
Experience with at least one common EDC system (e.g., Medidata Rave, Oracle Clinical).
Nice-to-haves:**
Certified Clinical Data Manager (CCDM®) certification from the Society for Clinical Data Management (SCDM).
Programming skills in SAS, R, or SQL.
Experience leading data management subprojects.
Personal qualities and mindset:**
Exceptional attention to detail and accuracy.
Strong analytical and problem-solving skills.
Excellent communication and teamwork skills for working in interdisciplinary study teams.
High level of autonomy, organizational talent, and sense of responsibility.
Ability to work precisely under time pressure and set priorities.
English
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