Data Quality Control Specialist. Clinical Biomarker Laboratory
Listed on 2026-05-11
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Quality Assurance - QA/QC
Data Analyst
The Role
Joining Moderna means advancing mRNA science to transform medicine. Work with exceptional global teams on a broad pipeline and build a career that makes a real difference for patients.
Moderna is establishing a leading research, development, and manufacturing facility at Harwell to support onshore mRNA vaccine production for respiratory diseases in the UK.
This long‑term investment will create skilled jobs and strengthen collaboration with academic, NHS, and government partners. We welcome experts ready to help expand access to life‑saving vaccines.
Within the Clinical Biomarker Laboratory, this role sits at the critical intersection of data integrity, regulatory compliance, and clinical development execution.
You will act as a key quality control partner, ensuring laboratory data generated in GCP‑regulated environments are inspection‑ready, fully traceable, and aligned to regulatory expectations.
Operating as an individual contributor, you will work hands‑on with complex datasets, laboratory systems, and cross‑functional stakeholders to uphold the highest standards of clinical data quality while supporting evolving digital and data‑driven capabilities, including exposure to advanced data tooling and automation.
Here’s What You’ll Do- Adhere to analytical data quality and integrity standards in accordance with MHRA, ICH, GCP requirements, applicable regulations, and established SOPs across clinical studies
- Perform comprehensive QC review of raw laboratory data (paper records, ELNs, instrument outputs, and electronic files), ensuring completeness, accuracy, and traceability to source data
- Review calculations and data processing steps, confirming mathematical accuracy, correct formula application, dilution factors, acceptance criteria, and statistical methods
- Ensure all calculations are reproducible from raw data and fully documented, including manual and system‑generated outputs
- Review laboratory documentation (worksheets, methods, SOPs, study plans, protocols, amendments, and source documents) for completeness, consistency, and compliance
- Conduct QC review of LIMS (Lab Vantage) entries, including sample metadata, test assignments, results, status changes, and approvals
- Verify accuracy of data transcription into LIMS and ensure consistency between LIMS, raw data, and source documentation
- Compare laboratory outputs against Data Transfer Specifications (DTS), ensuring correct structure, formatting, units, terminology, and completeness
- Verify transferred data accurately reflect approved results and meet study‑specific and sponsor‑defined requirements
- Review study plans, protocols, and reports to ensure alignment between planned work, executed laboratory activities, and reported outputs
- Identify discrepancies, missing data, or inconsistencies; document findings and issue QC observations in line with procedures
- Communicate data quality issues to scientific staff and study teams; support resolution through corrections, deviations, and CAPAs
- Ensure ALCOA+ data integrity principles are applied across the full data lifecycle (generation through archival)
- Verify compliance of electronic records and signatures with 21 CFR Part 11, EU Annex 11, and internal governance standards
- Contribute to deviation investigations, root cause analyses, and CAPA development related to data and documentation issues
- Support Excel workbook validation, including formula review, data integrity controls, versioning, and documentation practices
- Participate in review of protocols, analytical methods, reports, batch records, and GCP source documentation using systems such as Excel, Lab Vantage LIMS, and Veeva
- Support internal and external audits by providing data traceability evidence and responding to data‑related inquiries
- Collaborate with QA and cross‑functional teams to evolve the Quality Management System (QMS) and implement risk‑based quality approaches
- Coordinate with internal and external stakeholders to improve laboratory data quality, processes, and analytical workflows
- Deliver high‑quality, detail‑oriented work with efficiency in a fast‑paced, highly regulated laboratory environment
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