Director, AI & ML for Biomedical Discovery

Novartis AG; San Diego (CA); Presencial; USD 195.000 - 361.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

401(k) with company match

Comprehensive health benefits

Generous time off

Descripción de la vacante

Novartis AG is seeking a Director Data Science in San Diego, onsite, to lead the US DARe Data Science & AI efforts and shape the global AI strategy. The role focuses on integrating diverse data sources, defining a prioritized portfolio of initiatives, and driving impactful results across disease programs.

The candidate will lead development of biological foundation models, multimodal learning, and knowledge graphs, while building a high-performing team and collaborating across matrix

Formación

• PhD in Machine Learning, Computational Biology, Data Science, Computer Science, Systems Biology or related quantitative discipline.
• 10+ years applying advanced computational and AI approaches to biomedical research, drug discovery, or translational medicine.

Responsabilidades

• Lead the US DARe Data Science & AI efforts and shape the global AI and ML strategy.
• Define a prioritized portfolio of Data Science & AI initiatives and measure impact.
• Co-shape and drive data science and AI efforts across disease programs.
• Lead development and application of biological foundation models, multimodal learning, and knowledge graphs.
• Work at the intersection of genetics, clinical data, proteomics, transcriptomics, and imaging.
• Build and grow a high-performing US-based team spanning applied AI, ML, and computational biology.

Conocimientos

Python programming

Deep learning

Machine learning

Communication

Leadership

Educación

PhD in ML/Computational Biology/Data Science

Herramientas

TensorFlow/PyTorch

Git

Descripción del empleo

Novartis AG is seeking a Director Data Science in San Diego, onsite, to lead the US DARe Data Science & AI efforts and shape the global AI strategy. The role focuses on integrating diverse data sources, defining a prioritized portfolio of initiatives, and driving impactful results across disease programs.

The candidate will lead development of biological foundation models, multimodal learning, and knowledge graphs, while building a high-performing team and collaborating across matrix