Jobs at Novartis

Lead clinical data analytics to convert complex trial data into actionable insights. Partner with data quality, central monitoring and data management to enable risk‑based review, drive data quality improvements, implement analytics and visualization (Power BI/Spotfire), support anomaly detection, and accelerate study cycle times while ensuring regulatory data standards and governance.

Lead Corporate Affairs AI strategy and portfolio, deliver enterprise-grade generative AI solutions, build and manage an AI team, own governance, adoption, value realization, and represent Corporate Affairs in enterprise AI governance and executive forums.

Lead strategy and execution of technology, data, and AI for clinical development. Architect scalable platforms, integrate diverse data assets, industrialize AI/ML use cases, ensure regulatory compliance, oversee product roadmaps and vendor partnerships, and lead global cross-functional teams to accelerate evidence generation and clinical delivery.

The Associate Director of Web Analytics will lead the design, implementation, and optimization of GA4, GBQ, and GCP integrations, providing technical expertise and strategic direction for analytics initiatives to drive business impact and efficiency.

The Commercial Portfolio Lead drives portfolio strategy, partnerships, and lifecycle management to maximize value and ensure operational excellence across the product portfolio.

The Head of Data Governance will establish data governance frameworks, ensure compliance, and oversee the anonymization of patient data for secondary research, collaborating closely with data management teams.

Manage and deliver high-quality medical communications (manuscripts, reviews, abstracts, posters, slide sets, symposia content, reports) on time. Perform QC, manage up to two brands, maintain records and compliance, train colleagues, liaise with customers/vendors, and support publication planning and medical education materials.

Lead phenomics strategy and execution to integrate human genetics and real‑world data for target identification, patient stratification, and translational evidence. Build and lead multidisciplinary teams, develop scalable phenotype curation and modeling pipelines, ensure scientific rigor and reproducibility, influence data and tooling roadmaps, drive cross‑functional decision support, champion responsible data/AI use, publish and engage externally, and hire and develop global talent.

Lead global labelling for neuroscience products across lifecycle: develop and maintain core and market labelling, translate clinical and safety data into compliant content, drive cross-functional alignment, support health authority interactions, and implement approved labelling changes ensuring global consistency and traceability.

Provide administrative and secretarial support to the marketing team, help prepare basic promotional materials, maintain distributor data, organize reports and marketing samples, support customer satisfaction and compliance activities, and report product complaints or adverse events on time.

Lead global labelling content strategy for neuroscience assets, developing core and regional prescribing information. Translate scientific evidence into product claims, partner with regulatory, clinical, safety, medical and commercial teams, negotiate with health authorities, monitor regulatory and competitive changes, and build capability through coaching and quality oversight to ensure compliant, aligned global labelling.

Lead development and alignment of global labelling strategy and content for oncology products across lifecycle stages. Drive creation of core and major market labelling documents, present recommendations to governance bodies, anticipate and mitigate labelling risks, support health authority interactions, and mentor colleagues while ensuring inspection readiness and continuous improvement.

Lead development and maintenance of global labelling strategy and content for established medicinal products. Guide cross-functional alignment, prepare regulatory-facing labelling documents and health authority responses, anticipate and mitigate labelling risks, present recommendations to governance bodies, and mentor colleagues to ensure inspection readiness and high-quality, compliant labelling across markets.

Lead a campaign tagging team to design and implement tagging and UTM strategies, train stakeholders on Claravine, manage QA for email campaigns (SFMC/HQE/RTE), act as Deputy Product Owner for tagging product delivery, collaborate with agencies and cross-functional teams, and drive measurement improvements.

Lead and strengthen the Ethics, Risk & Compliance program for Novartis Ireland. Advise senior leaders, drive risk identification and mitigation, promote Speak Up culture, ensure audit readiness and regulatory adherence, deliver compliance training, and build internal and external partnerships to protect integrity and reputation.

The Sales and Marketing Head for Immunology leads commercial strategies, executes marketing plans, engages customers, and builds high-performing teams to achieve growth in the therapeutic area.

Lead integrated commercial strategy and execution for a Therapeutic Area, focusing on brand strategy, sales execution, and cross-functional collaboration.

Lead design and delivery of learning programs for Trial Master File (TMF) and clinical document governance. Develop metrics and knowledge frameworks, partner cross-functionally, support audit/inspection readiness, drive adoption of documentation standards, and manage capability-building initiatives to improve TMF health globally.

Lead strategy, planning, and execution of clinical document migrations (eTMF/eDMS). Partner with stakeholders and vendors, manage governance, incidents, change control, resource forecasting, audits/inspections support, and drive continuous improvement of migration processes and tools.

Lead development of advanced ML and deep learning methods for drug discovery. Design, implement, and scale AI models and foundation-model adaptations, collaborate with scientists to translate outputs into hypotheses, track model impact, and drive cross-functional adoption of AI solutions.