Senior Manager R&D Quality Analytics & Portfolio Insights [Remote]

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Manager R&D Quality Analytics & Portfolio Insights based in the United States.

This role offers the opportunity to transform healthcare research through advanced analytics, technology, and data-driven quality oversight.
The Senior Manager will apply statistical methods, automation, and emerging technologies to identify risks and generate actionable insights across regulated R&D activities.
You will help strengthen clinical development, patient safety, data integrity, and compliance by translating complex information into strategic recommendations.
The position combines expertise in quality, life sciences, analytics, and technology to support smarter decision-making across global research programs.
You will collaborate with multidisciplinary teams and influence how organizations use data to improve quality management and operational excellence.
This is an impactful opportunity for a data-driven professional passionate about innovation, regulatory excellence, and improving outcomes for patients worldwide.

Accountabilities:

The Senior Manager R&D Quality Analytics & Portfolio Insights will develop and implement advanced analytical approaches that enhance independent quality oversight across regulated research and development activities. The role focuses on identifying emerging risks, building scalable analytics solutions, and translating complex data into meaningful quality insights that support proactive decision-making.

• Partner with R&D Quality leaders and cross-functional stakeholders to identify quality priorities, oversight opportunities, emerging risks, and areas requiring proactive intervention.
• Develop and maintain analytical frameworks, quality indicators, risk signals, thresholds, and monitoring approaches aligned with risk-based quality management and Quality by Design principles.
• Analyze clinical, safety, laboratory, monitoring, vendor, audit, operational, and quality data to identify study-level, program-level, and portfolio-level trends.
• Create statistical monitoring approaches, predictive models, anomaly detection methods, dashboards, and automated solutions to support quality oversight.
• Design and maintain analytical tools using technologies such as SQL, R, Python, Power BI, and other approved platforms.
• Translate business and quality requirements into analytical objectives, data specifications, implementation plans, and measurable outcomes.
• Perform data profiling, transformation, reconciliation, and root-cause analysis to ensure accuracy, reliability, and consistency of analytical outputs.
• Support patient safety monitoring by identifying potential risks related to adverse-event reporting, protocol compliance, data quality, and operational performance.
• Apply analytics to support GCP, GVP, GLP, and GCLP oversight activities, including audit readiness, vendor oversight, and inspection preparation.
• Establish governance practices for analytical and AI-enabled solutions, including documentation, validation, explainability, access controls, and lifecycle management.
• Create executive-level reports, visualizations, and recommendations that communicate quality risks and opportunities clearly.
• Lead analytics initiatives from initial problem definition through development, implementation, adoption, and continuous improvement.
• Collaborate with Clinical Operations, Clinical Development, Data Management, Biometrics, Pharmacovigilance, Regulatory Affairs, technology teams, and other stakeholders.
• Stay current with regulatory expectations, industry trends, statistical methods, responsible AI practices, and emerging technologies relevant to R&D quality.

Requirements:

The ideal candidate combines expertise in life sciences, R&D quality, analytics, and technology, with the ability to solve complex problems and communicate insights effectively across technical and business audiences.

• Experience in pharmaceutical, biotechnology, clinical research, healthcare, or another regulated life sciences environment.
• Strong knowledge of R&D Quality, clinical quality, quality assurance, compliance, risk management, or regulated research operations.
• Strong understanding of GCP and ICH requirements, with familiarity with GVP, GLP, GCLP, data integrity, and computerized system assurance.
• Experience working with structured and unstructured data, including data mapping, cleaning, transformation, reconciliation, and modeling.
• Hands-on experience applying statistical analysis, central monitoring, anomaly detection, predictive analytics, machine learning, natural language processing, or generative AI to healthcare or quality-related challenges.
• Advanced proficiency with SQL and practical experience using R or Python.
• Experience with Power BI or similar business intelligence and data visualization platforms.
• Familiarity with APIs, cloud platforms, ETL/ELT workflows, data warehouses, Git or comparable version-control systems, and analytical development environments.
• Experience with automation, AI-enabled tools, model deployment, or analytical monitoring solutions is preferred.
• Ability to translate complex R&D processes into scalable analytical solutions while maintaining regulatory and scientific relevance.
• Strong written, verbal, and presentation skills, with the ability to communicate technical findings to non-technical stakeholders.
• Ability to collaborate effectively across global, multidisciplinary teams.
• Ability to handle confidential clinical, safety, quality, and patient-related information appropriately.
• Strong analytical thinking, problem-solving abilities, and attention to detail.
• Ability to provide technical leadership and guidance to project teams, vendors, contractors, or analysts.
• Willingness to travel up to 20%.

Benefits:

The company offers competitive compensation and a global environment focused on innovation, collaboration, and professional growth.

• Competitive salary ranges depending on location:
  • Switzerland: approximately CHF 141,800 – CHF 177,300 annually.
  • United Kingdom: approximately £74,500 – £93,100 annually.
  • Germany: approximately €94,500 – €118,100 annually.
• Opportunity to work remotely within eligible locations.
• Global, collaborative work environment supporting innovative healthcare solutions.
• Professional development opportunities and continuous learning culture.
• Exposure to advanced analytics, AI technologies, and cutting-edge research initiatives.
• Opportunity to contribute to projects focused on improving patient safety and healthcare outcomes.
• Inclusive workplace culture centered on teamwork, innovation, and excellence.
• Opportunities to collaborate with international teams across research, quality, technology, and healthcare functions.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.