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# Director, AI and Machine Learning for Biology

- **Company:** Novartis AG
- **Location:** San Diego County, CA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Bioinformatics, Computational Biology, Python (Programming Language), Machine Learning, Multimodal Learning, Large Language Models, Deep Learning, Electronic Medical Records, Generative AI, Information Technology, Machine Learning Operations, Feature Extraction, Software Version Control
- **Published:** October 26, 2026
- **Apply:** https://www.careerbuilder.com/job-details/director-ai-and-machine-learning-for-biology-la-jolla-ca--a5a97058-7569-43d7-9207-2abf0b0ea387

## About the Role

Machine Learning, Artificial Intelligence (AI), Biology, Leadership, Data Science, Artificial Intelligence (AI), Biology, Ontology, Proteomics, Organizational Skills, and establish external partnerships that accelerate DARe''s AI capabilities.Translate scientific questions into computational strategies, selecting fit-for-purpose statistical, machine learning, AI, and bioinformatics approaches.Build strong organizational connectivity to ensure effective collaboration, knowledge sharing, and execution and foster a one-team culture across geographies and scientific disciplinesDrive AI adoption across the departmentPartner closely with internal functions including Data and Digital, Discovery Sciences and Disease areasEssential Requirements:PhD in Machine Learning, Computational Biology, Data Science, Computer Science, Systems Biology or a related quantitative discipline combined with a deep understanding of biology10+ year experience applying advanced computational and AI approaches to biomedical research, drug discovery, or translational medicine.Proven success leading multidisciplinary global teams across AI, human data, and experimental
scienceDemonstrated experience developing or applying advanced machine-learning approaches to complex biological data, such as foundation models, representation learning, generative models, or multimodal learning across sequence, single-cell, spatial, imaging, or other biomedical data.Strong working knowledge of deep learning, representation learning, multi-modal AI, generative AI, large-scale biological data modelingStrong experience in large-scale model training, distributed computation, model adaptation, and deployment within machine learning operations frameworksStrong coding proficiency in Python and deep learning frameworks, with experience using version control systems.Experience with omics data (transcriptomics, proteomics, metabolomics) and cellular imaging dataAbility to lead and influence across matrix organizations with exceptional communication and stakeholder management skills.Demonstrated ability to operate effectively in a fast-paced and highly collaborative research

## Description

The Director, Data Science & AI will shape and execute DARe's global AI strategy, lead its US data science capability, and connect computational, experimental, and translational teams and external partners to accelerate target discovery and strengthen DARe's scientific leadership., Internal Job Title: Director Data SciencePosition Location: San Diego, California, onsiteAbout the Role:DARe is building an AI-enabled discovery engine that integrates longitudinal human data, genetics, multi-omics, imaging, and advanced biological models to uncover causal drivers of aging, resilience, and regeneration. Our goal is to translate these insights into differentiated novel therapeutic targets and medicines for age-related diseases.We are seeking an exceptional scientific and technical leader to shape DARe's global Data Science & AI strategy and build our US capability in San Diego. The successful candidate will combine strategic leadership with technical depth to guide high-impact AI programs, connect computational and experimental science, and translate emerging capabilities into meaningful drug-discovery decisions.Key Responsibilities: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, establish clear measures of scientific and operational impact, and ensure that investments translate into better target decisions, stronger experimental design, and accelerated discovery.Co-shape and drive data science and AI efforts supporting target identification, target prioritization, and validation across disease programs and contribute to the DARe long-term scientific AI visionLead the development and application of biological foundation models, multimodal learning, biomedical knowledge graphs, and agentic workflows to drive evidence integration and target prioritizationWork at the intersection of human genetics, longitudinal clinical trajectories, proteomics, transcriptomics, metabolomics, imaging, and electronic health record data.Build, lead, and develop a high-performing US-based team spanning applied AI, machine learning, computational biology, and data science, while creating meaningful growth opportunities for early-career talent.Evaluate emerging technologies