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Data Science Leader
2 months ago
About the Role
We are seeking a highly skilled Data Science Leader to join our Multimodal Data & Analytics group at Novartis Farmacéutica. As an Associate Director Data Science, you will play a key role in shaping data science, biomarker, and AI strategies applied to patient-level data.
Key Responsibilities
- Provide global strategic data science leadership to clinical development programs of medium to high complexity, leveraging relevant technical and disease area knowledge.
- Develop, plan, execute, interpret, validate, and communicate innovative exploratory biomarker and/or AI analyses and algorithms to facilitate internal decision making and support submissions of candidate drug and associated companion diagnostics packages.
- Provide technical expertise in data science and (predictive) machine learning/AI as well as domain knowledge in biology and/or medicine to identify and develop opportunities for influencing internal decision making and discussions on white papers/regulatory policy.
- Perform hands-on analysis of integrated clinical, outcomes, and high-dimensional, patient-level biomarker data from clinical trials and the real world, including genomics, transcriptomics, proteomics, and flow cytometry.
- Proactively use internal networks to drive the use of innovative ML, AI, or other methods, including through materials for internal decision boards/regulatory/submission documents.
- Influence the Analytics team and cross-functional partners in research, regulatory, clinical, and commercial teams on the content of the biomarker and/or AI strategy, execution, and delivery of assigned projects.
- Shape training materials and internal automation initiatives.
- Track record of shaping policy and best practices for innovative approaches such as data science, AI, or precision medicine.
- Scientific leadership skills demonstrated in facilitating and optimizing clinical development strategy, including global scientific leadership in the development and evaluation of modern program/trial design methodologies.
- Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods, design of clinical trials, and GxP environments.
- Familiarity with statistical and analytical methods for genetics and -omics data analysis and working knowledge of high-dimensional biomarker platforms.
- Strong programming skills in R and Python, with demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling.
- Excellent interpersonal and communication skills (verbal and writing).
Why Novartis Farmacéutica
We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.
