Senior Principal Data Scientist

Senior Principal Data Scientist role at Novartis. In this role, you will understand complex business problems, formulate integrated analytical approaches to mine data sources, employ statistical methods and machine learning algorithms to contribute to solving unmet medical needs in neuroscience, discover actionable insights, and automate processes to reduce effort and time for repeated use. You will manage the data lifecycle of enterprise data from acquisition through enrichment, consumption, retention, and retirement, ensuring useful, clean, and accurate data throughout its lifecycle. You will translate findings to business users with clear impact using presentations, smart visualizations, and contextual storytelling.

About The Role: Our Development Team is guided by our purpose to reimagine medicine to improve and extend people’s lives. We are optimizing processes, investing in new technologies, and building depth and capabilities to bring medicines to patients faster. We seek key talent to help give people with disease and their families a brighter future. Apply today and join a collaborative environment.

As a Senior Principal Data Scientist in the Advanced Quantitative Scientists group, you will discuss and implement data science and high-dimensional modelling methodologies on patient-level data (including biomarker, clinical, and outcomes data) across clinical development in Neuroscience. You will combine data science and AI skills with scientific knowledge in biology, imaging, or medicine to inform drug development decisions in collaboration with internal and external partners.

This role offers hybrid working, requiring 3 days per week or 12 days per month in our London Office.

• Provide global strategic data science leadership and support to clinical development programs of low to mid complexity, based on technical and disease-area knowledge.
• Contribute to planning, execution, interpretation, validation and communication of exploratory biomarker and AI analyses and algorithms to facilitate internal decision making and support submissions of candidate drugs and research collaborations.
• Provide technical expertise in data science and predictive machine learning/AI, as well as domain knowledge in biology and/or medicine to identify opportunities influencing internal decision making and research collaborations.
• Perform hands-on analysis of integrated clinical, imaging, digital, fluid biomarker outcomes and high-dimensional, patient-level data from trials and real-world sources to generate evidence for decision making in drug development.
• Contribute to scientific content for internal decision boards, regulatory documents, trial design, and peer-reviewed publications.
• Align with and influence the Analytics team and cross-functional partners on biomarker and/or AI strategy, execution, and delivery of assigned projects.

• Ph.D. in data science, biostatistics, pharmacology, bioinformatics, mathematics, or other quantitative field (or equivalent).
• Experience in clinical drug development with extensive exposure to clinical trials.
• Clinical, pharmacological, and therapeutic knowledge in neuroscience.
• Good understanding of clinical study design principles and familiarity with clinical data in a clinical trial (GxP) setting.
• Strong knowledge of statistical methods (e.g., time-to-event analysis), machine learning/AI, meta-analysis, mixed effects, longitudinal modelling, Bayesian methods, variable selection methods, and design of clinical trials.
• Familiarity with high-dimensional data methods (e.g., imaging, digital, genetics or -omics).
• Strong programming skills in R and Python, with experience in data visualization, exploratory analysis, and predictive modeling.
• Excellent interpersonal and communication skills (verbal and writing) and ability to deliver clear presentations for decision-making.

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

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