Senior Manager, R&D Quality Analytics – Portfolio Insights

This is a fully remote position, open to applicants in Switzerland, +2 more states.

📋 Description

• Collaborate with R&D Quality leadership and stakeholders in GCP, GVP, GLP, and GCLP to pinpoint quality inquiries, emerging risks, oversight gaps, and opportunities for intervention.

• Execute analyses across studies, programs, vendors, and processes to uncover recurring, systemic, and portfolio-level risks.

• Create and sustain quality indicators, critical-to-quality factors, quality tolerance limits, risk indicators, thresholds, escalation criteria, and portfolio surveillance techniques.

• Integrate and evaluate data from clinical, safety, pharmacovigilance, laboratory, monitoring, audit, inspection, vendor, system, and quality sources.

• Develop analytics for audit planning, patient-safety and subject-protection risk identification, as well as GLP/GCLP and GVP oversight.

• Design, develop, test, implement, and maintain statistical packages, analytical applications, dashboards, automated workflows, predictive models, and decision-support tools.

• Conduct data profiling, mapping, cleaning, transformation, source-to-report reconciliation, and root-cause analysis.

• Govern analytical and AI-enabled solutions through intended-use documentation, data lineage, testing, validation or assurance, access controls, version control, change management, human review, explainability, performance monitoring, and retirement planning.

• Produce executive-ready visualizations, quality narratives, risk summaries, and actionable recommendations.

• Assist in Quality Management Review, portfolio quality surveillance, RBQM governance, audit planning, inspection readiness, vendor oversight, computerized-system oversight, and ongoing improvement.

• Collaborate with teams in Clinical Operations, Clinical Development, Data Management, Biometrics, Medical Monitoring, Pharmacovigilance, Regulatory Affairs, laboratory, RBQM, audit, technology, data engineering, and platform initiatives.

• Lead or coordinate analytics workstreams from problem identification through to development, testing, implementation, adoption, monitoring, and benefit realization.

• Remain up-to-date with R&D regulatory expectations, industry practices, statistical methodologies, responsible AI principles, and emerging technologies.

⛳️ Requirements

• Experience in pharmaceutical, biotechnology, clinical research, healthcare, or another regulated life-sciences field.

• Demonstrated expertise in R&D Quality, clinical quality, quality assurance, compliance, risk management, or regulated research and development operations.

• Strong working knowledge of GCP and ICH standards.

• Familiarity or experience in GVP, GLP, GCLP, data integrity, computerized-system assurance, and global R&D Quality expectations.

• Experience with both structured and unstructured data, including data mapping, cleaning, reconciliation, transformation, data modeling, automated quality checks, and data pipelines.

• Proficient in applying statistical analysis, central statistical monitoring, anomaly detection, forecasting, predictive modeling, machine learning, natural-language processing, generative AI, or related methodologies to clinical, safety, research, or quality challenges.

• Ability to convert complex R&D Quality and operational processes into scalable technical solutions.

• Skill in clearly communicating technical findings to non-technical stakeholders and transforming analyses into actionable quality recommendations.

• Advanced proficiency in SQL and hands-on experience with R or Python.

• Familiarity with Power BI or similar visualization and business-intelligence platforms.

• Experience with statistical programming, central monitoring, anomaly detection, predictive modeling, or machine-learning tools and techniques.

• Knowledge of APIs, data warehouses, cloud platforms, ETL/ELT workflows, Git or similar version-control systems, and analytical development environments.

• Preferred experience with automation, natural-language processing, generative AI, or model deployment and monitoring tools.

• Proficient in Microsoft Office applications.

• Exceptional written, verbal, presentation, and interpersonal communication abilities.

• Capacity to collaborate across global, cross-functional, clinical, safety, research, quality, data, and technical teams.

• Ability to handle sensitive or confidential clinical, safety, quality, laboratory, and patient-level information in compliance with applicable regulations.

• No direct people-management responsibilities are required; may offer technical leadership, mentoring, and work direction.

• Willingness to travel up to 20% may be necessary.

🏝️ Benefits

• Travel may be required up to 20%.

• Equal opportunity employment.

• Chance to work for a global oncology organization.

• Collaboration with a worldwide team across six continents.