Principal Risk Quality Management Data Monitor

About This Role

Principal Risk Based Quality Management Data Monitor – play a critical role in shaping how clinical trial data is monitored, protected, and elevated to the highest quality standards. Implement Risk-Based Quality Management (RBQM) strategies to ensure patient safety, regulatory compliance, and data integrity across all phases of clinical research. Collaborate closely with biostatistics, data science, safety/pharmacovigilance, clinical operations, and vendors to detect and triage signals early, optimize KRIs/QTLs, and drive continuous process and technology improvements across the portfolio.

• Partner with cross‑functional teams to identify critical data and processes (CDPs) and associated study risks.
• Support the development and maintenance of the study‑specific Risk Assessment Categorization Tool (RACT) or equivalent.
• Prioritize risks and signals based on patient safety impact, data integrity, severity, likelihood, and detectability.
• Conduct proactive, ongoing data reviews using RBQM dashboards and analytics tools.
• Ensure timely escalation and follow‑up on any signals or anomalies.
• Triage: prioritize, elevate, and track signals.
• Review and validate data across EDC, safety, and other clinical systems to ensure consistency and quality.
• Oversee data cleaning timelines and ensure adherence to risk mitigation plans.
• Partner with study teams to ensure data flow mapping supports early risk detection.
• Document and communicate findings clearly and effectively to study teams.
• Trigger or support Corrective and Preventive Actions (CAPA).
• Participate in root‑cause analyses for major deviations or quality concerns.
• Ensure alignment with ICH‑GCP, FDA/EMA regulations, and internal SOPs.
• Support audit and inspection readiness related to RBQM and centralized monitoring.
• Contribute to process enhancements, technology upgrades, and RBQM best practices.
• Partner with platform/analytics teams to enhance dashboards and detection logic; perform UAT and help shape product roadmaps.
• Provide training, guidance, and mentorship on RBQM concepts to study teams.

Data‑driven problem solver with deep understanding of clinical trial operations. Excel in fast‑paced, matrixed environments, collaborating with diverse teams. Spot data issues before they escalate, anticipate risk, communicate insights clearly, drive actions, and continuously improve processes. Balance rigor with pragmatism, communicate crisply across functions, and stay laser focused on patient safety and data integrity.

• 5+ years of experience in clinical data management, clinical operations or academia with strong scientific knowledge in at least one therapeutic area within the Biogen portfolio.
• RBQM‑focused roles within pharma or CRO settings.
• Hands‑on experience with centralized monitoring tools (RBQM platforms/dashboards), KRIs, QTLs, or similar RBQM methodologies.
• Proficiency with EDC systems and data visualization tools.
• High attention to detail with proven ability to manage multiple, competing priorities.
• Experience supporting audits/inspections.
• Understanding of clinical data flow, study endpoints, and regulatory requirements.
• Strong analytical and critical‑thinking abilities.
• Excellent communication and stakeholder management skills.
• Ability to adapt and thrive in a dynamic, cross‑functional environment.
• Risk‑based thinking and structured problem‑solving.
• Data‑driven decision‑making.
• Collaborative teamwork across clinical and operational functions.
• Deep understanding of drug development and biopharmaceutical industry required.
• Fluent English (oral and written).
• Demonstrated ability to identify data trends, signals, outliers, and risk indicators using listings, visualizations, metrics, and analytics tools.
• Strong knowledge of GCP, ICH E6(R2)/E6(R3), regulatory expectations, and industry data quality best practices.
• Demonstrated problem‑solving skills with a continuous improvement mindset and enthusiasm for scientific data excellence.

• Bachelor’s degree in life sciences, health sciences, pharmacy, nursing, data science, or related discipline; advanced degree (MS, PharmD, PhD) strongly preferred.
• Experi…