Job description

Band Level 6 Job Description Summary 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. Job Description Internal Job Title: Director Data Science Position Location: San Diego, California, onsite About 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 vision Lead the development and application of biological foundation models, multimodal learning, biomedical knowledge graphs, and agentic workflows to drive evidence integration and target prioritization Work 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 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 disciplines Drive AI adoption across the department Partner closely with internal functions including Data and Digital, Discovery Sciences and Disease areas Essential Requirements: PhD in Machine Learning, Computational Biology, Data Science, Computer Science, Systems Biology or a related quantitative discipline combined with a deep understanding of biology 10 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 science Demonstrated 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 modeling Strong experience in large-scale model training, distributed computation, model adaptation, and deployment within machine learning operations frameworks Strong coding proficiency in Python and deep learning frameworks, with experience using version control systems. Experience with omics data (transcriptomics, proteomics, metabolomics) and cellular imaging data Ability 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 environment. Desirable Requirements: Expertise in statistical genetics, including genome-wide association studies, rare variants, Mendelian randomization, colocalization, or fine-mapping Understanding of modern data foundations including ETL/ELT pipelines, biomedical ontologies, metadata standards, data governance, and FAIR data principles. Expertise in diseases of aging, neurodegeneration, cardiometabolic disease, regeneration biology, or related therapeutic areas. Experience with knowledge graph technologies and scientific knowledge integration platforms. Experience with developing biological aging clocks Compensation and Benefits: The salary for this position is expected to range between $194,600 and $361,400 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves. To learn more about the culture, rewards and benefits we offer our people click here . EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential. Accessibility and reasonable accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to tas.nacomms novartis.com call 1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message. novartis.com Salary Range $194,600.00 - $361,400.00 Skills Desired Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Stakeholder Engagement, Statistical Analysis, Time Series Analysis

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Job Description Summary
Internal Job Title: Director Data Science
Position Location: San Diego, California, onsite
Lead the US DARe Data Science & AI efforts and shape the global AI and ML strategy
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 vision
Lead the development and application of biological foundation models, multimodal learning, biomedical knowledge graphs, and agentic workflows to drive evidence integration and target prioritization
Work 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 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 disciplines
Drive AI adoption across the department
Partner closely with internal functions including Data and Digital, Discovery Sciences and Disease areas
PhD in Machine Learning, Computational Biology, Data Science, Computer Science, Systems Biology or a related quantitative discipline combined with a deep understanding of biology
10 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 science
Strong working knowledge of deep learning, representation learning, multi-modal AI, generative AI, large-scale biological data modeling
Strong experience in large-scale model training, distributed computation, model adaptation, and deployment within machine learning operations frameworks
Strong coding proficiency in Python and deep learning frameworks, with experience using version control systems.
Experience with omics data (transcriptomics, proteomics, metabolomics) and cellular imaging data
Ability 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 environment.
Expertise in statistical genetics, including genome-wide association studies, rare variants, Mendelian randomization, colocalization, or fine-mapping
Understanding of modern data foundations including ETL/ELT pipelines, biomedical ontologies, metadata standards, data governance, and FAIR data principles.

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aimlmachine learningpythonaccessibility

Platform: workday
Effort: long

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401(K)

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