... metadata, data lineage, access, retention, and version control in alignment with ICH-GCP, data ... automation libraries, training materials, and best practices that reduce rework and support ...
... metadata, data lineage, access, retention, and version control in alignment with ICH-GCP, data ... automation libraries, training materials, and best practices that reduce rework and support ...
... metadata, data lineage, access, retention, and version control in alignment with ICH-GCP, data ... automation libraries, training materials, and best practices that reduce rework and support ...
... metadata, data lineage, access, retention, and version control in alignment with ICH-GCP, data ... automation libraries, training materials, and best practices that reduce rework and support ...
Metadata Library information
What are metadata librarians and what do they do?
What is the difference between Metadata Library vs Metadata Specialist?
| Aspect | Metadata Library | Metadata Specialist |
|---|---|---|
| Credentials | Typically requires a degree in library science, information management, or related fields | Requires similar credentials, often with additional certifications in data management or information systems |
| Work Environment | Libraries, archives, or information centers managing large metadata collections | Data-driven organizations, digital repositories, or information management teams |
| Employer & Industry | Libraries, museums, archives, academic institutions | Tech companies, publishing, digital content providers |
| Search & Comparison Intent | Understanding library metadata management roles | Specialized data and metadata management tasks |
The main difference is that a Metadata Library focuses on managing metadata within library and archival settings, while a Metadata Specialist handles metadata in broader digital and data environments. Both roles require similar credentials but serve different industry needs.
What are some common challenges faced by professionals working in a metadata library role, and how can they be addressed?
What are the key skills and qualifications needed to thrive as a Metadata Librarian, and why are they important?
Other
Medical, Dental, Vision, Life, Retirement, PTO
Posted 14 days ago
Reckitt rating
8.7
Based on 20 frontline employees who took The Breakroom Quiz
Job description
We do the right thing, always, by ensuring we act with responsibility and integrity, by complying with regulatory legislation across the globe, whilst ensuring our products are safe for our consumers and are to the highest quality.
The size of our organisation means you'll have the opportunity to learn and work in different functions within R&D, giving you exposure to different disciplines, teams and environments. You will also have access to our Research and Development Academy, designed to develop our team and allow you to grow in our great organisation.
The Clinical Data & Statistical Technology Specialist designs, manages, and modernizes clinical data collection and analysis-ready data workflows for nutrition clinical studies. This role bridges Clinical Operations, Data Management, Biostatistics, Medical Science, and external partners to ensure study data are high quality, traceable, compliant, and ready for statistical analysis and reporting. The role has evolved beyond traditional clinical database design to include applied statistical support, data governance, vendor oversight, and responsible use of approved automation, AI-enabled workflows, dashboards, and analytics tools.
- Design and maintain clinical data systems: Translate protocols, endpoints, and statistical analysis requirements into eCRFs, database structures, edit checks, validation rules, visit schedules, data transfer specifications, and data review plans.
- Support statistical analysis readiness: Partner with the Statistician to prepare, review, and validate analysis-ready data extracts, listings, descriptive summaries, reconciliation outputs, derivation logic, outlier checks, missing data checks, and other quality control outputs.
- Drive data quality and compliance: Coordinate data review, discrepancy management, external data reconciliation, database lock readiness, audit-ready documentation, controlled terminology, metadata, data lineage, access, retention, and version control in alignment with ICH-GCP, data privacy, security, and SOP expectations.
- Enable technology, automation, and AI: Identify and maintain approved tools, dashboards, automated checks, data quality monitoring approaches, and AI-assisted workflows that improve efficiency, consistency, scalability, and insight generation while preserving validation, documentation, human oversight, and auditability.
- Manage vendors and external data flows: Provide oversight of CROs, EDC vendors, external laboratories, ePRO/eCOA providers, wearables, and other data providers to ensure data transfers, quality checks, issue resolution, and timelines are managed effectively.
- Strengthen standards and knowledge continuity: Maintain and improve standards, templates, data dictionaries, validation checklists, reusable code or automation libraries, training materials, and best practices that reduce rework and support consistent study execution.
- Bachelor's degree in a quantitative or health-related field (e.g., statistics, data science, clinical research) required; Master's preferred or equivalent experience considered.
- Demonstrated training or applied experience in biostatistics, statistical methods, epidemiology, or clinical data analysis.
- Minimum 3 years of experience in clinical data management, database design, statistical programming support, analytics, or clinical research (healthcare/pharma preferred).
- Working knowledge of clinical trial processes, including eCRF design, database build, data cleaning, endpoint collection, database lock, and study reporting.
- Understanding of statistical concepts for clinical research, including data structures, analysis populations, derived variables, summaries, and quality control.
- Proficiency with EDC/CDMS platforms, SQL, and at least one analytical tool (e.g., SAS, R, Python).
- Familiarity with regulatory standards and practices, including ICH-GCP, data integrity, privacy/security, and SOP-driven environments.
- Strong analytical, communication, and organizational skills; ability to manage multiple priorities, collaborate cross-functionally, and meet deadlines.
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