Senior Manager, R&D Quality Analytics – Portfolio Insights

🕒 Yesterday

🌐 Switzerland, United Kingdom, +1 more countries – Remote

🇨🇭 Switzerland – Remote 🇬🇧 United Kingdom – Remote 🇩🇪 Germany – Remote

💵 CHF141.8k - CHF177.3k / year

⏰ Full Time

🟠 Senior

👔 Manager

👻 Ghost score 0%

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BeOne Medicines

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2010

🧬 Biotechnology

🏥 Healthcare

💊 Pharmaceuticals

Biotechnology • Healthcare • Pharmaceuticals

BeOne Medicines is a global oncology company domiciled in Switzerland that is discovering and developing innovative treatments that are more affordable and accessible to cancer patients worldwide. With a portfolio spanning hematology and solid tumors, BeOne is expediting the development of its diverse pipeline of novel therapeutics through its internal capabilities and collaborations. With a growing global team of more than 11,000 colleagues spanning six continents, the Company is committed to radically improving access to medicines for far more patients who need them.

📋 Description

• Partner with R&D Quality leadership and GCP, GVP, GLP, and GCLP stakeholders to identify priority quality questions, emerging risks, oversight gaps, and intervention opportunities • Apply quality, regulatory, scientific, and operational context to analytical methods • Conduct cross-study, cross-program, cross-vendor, and cross-process analyses to identify systemic and portfolio-level risks • Develop and maintain quality indicators, critical-to-quality factors, quality tolerance limits, risk indicators, thresholds, escalation criteria, and portfolio surveillance methods • Integrate and analyze clinical, safety, pharmacovigilance, laboratory, monitoring, audit, inspection, vendor, system, and quality data • Develop analytics for audit planning, patient-safety and subject-protection risks, GLP/GCLP oversight, and GVP oversight • Translate R&D Quality and business needs into analytical objectives, data requirements, specifications, acceptance criteria, implementation plans, and outcomes • Design, develop, test, implement, and maintain statistical packages, analytical applications, dashboards, automated workflows, predictive models, and decision-support tools • Use automation, machine learning, natural-language processing, generative AI, and emerging methods where fit for purpose • Perform data profiling, mapping, cleaning, transformation, 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 • Maintain technical and quality documentation for reproducibility, traceability, inspection readiness, and fitness for purpose • Create executive-ready visualizations, quality narratives, risk summaries, and recommendations • Support Quality Management Review, portfolio quality surveillance, RBQM governance, audit planning, inspection readiness, vendor oversight, computerized-system oversight, and continuous improvement • Partner with Clinical Operations, Clinical Development, Data Management, Biometrics, Medical Monitoring, Pharmacovigilance, Regulatory Affairs, laboratory, RBQM, audit, technology, data engineering, and platform teams • Lead or coordinate analytics workstreams from problem framing through development, testing, implementation, adoption, monitoring, and benefit realization • Stay current with global R&D regulatory expectations, industry practices, statistical methods, responsible AI principles, and emerging technologies

🎯 Requirements

• Experience in pharmaceutical, biotechnology, clinical research, healthcare, or another regulated life-sciences environment • Demonstrated knowledge of R&D Quality, clinical quality, quality assurance, compliance, risk management, or regulated research and development operations • Strong working knowledge of GCP and ICH requirements • Familiarity or experience in GVP, GLP, GCLP, data integrity, computerized-system assurance, and global R&D Quality expectations • Experience with structured and unstructured data, data mapping, data cleaning, reconciliation, transformation, data modeling, automated quality checks, and data pipelines • Experience applying statistical analysis, central statistical monitoring, anomaly detection, forecasting, predictive modeling, machine learning, natural-language processing, generative AI, or related methods • Ability to translate complex R&D Quality and operational processes into scalable technical solutions • Ability to communicate technical findings clearly to nontechnical stakeholders • Advanced proficiency with SQL and hands-on proficiency with R or Python • Experience with Power BI or comparable visualization and business-intelligence platforms • Experience with APIs, data warehouses, cloud platforms, ETL/ELT workflows, Git or comparable version-control tools, and analytical development environments • Proficiency with Microsoft Office applications • Excellent written, verbal, presentation, and interpersonal communication skills • Ability to collaborate across global, cross-functional, clinical, safety, research, quality, data, and technical teams • Ability to work with sensitive or confidential information in accordance with applicable requirements • No direct people-management responsibility is required; may provide technical leadership, coaching, and work direction

🏖️ Benefits

• Equal opportunity employment • Up to 20% travel may be required