Director, AI and Machine Learning for Biology

Novartis • Annandale, NJ

3d • $194,600 - $361,400 • Onsite

About The Position

The Director, Data Science & AI will shape and execute DARe’s global AI strategy, lead its US data science capability in San Diego, and connect computational, experimental, and translational teams and external partners to accelerate target discovery and strengthen DARe’s scientific leadership. DARe is building an AI-enabled discovery engine integrating longitudinal human data, genetics, multi-omics, imaging, and advanced biological models to uncover causal drivers of aging, resilience, and regeneration and translate these insights into therapeutic targets and medicines for age-related diseases.

This scientific and technical leadership role combines strategic direction with hands-on technical depth. The Director will guide high-impact AI programs, lead the development and application of advanced computational approaches, and translate emerging capabilities into meaningful drug-discovery decisions. The role also entails building and developing a high-performing US team and fostering collaboration across geographies and scientific disciplines.

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+ years of 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, multimodal AI, generative AI, and 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, including transcriptomics, proteomics, and 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, highly collaborative research environment.

Nice To Haves

• 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 developing biological aging clocks.

Responsibilities

• Lead the US DARe Data Science & AI efforts and shape the global AI and machine-learning strategy.
• Define a prioritized portfolio of Data Science & AI initiatives, establish measures of scientific and operational impact, and ensure investments improve target decisions and experimental design and accelerate discovery.
• Co-shape and drive data science and AI efforts supporting target identification, prioritization, and validation across disease programs, contributing to DARe’s long-term scientific AI vision.
• Lead development and application of biological foundation models, multimodal learning, biomedical knowledge graphs, and agentic workflows for evidence integration and target prioritization.
• Work across 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 growth opportunities for early-career talent.
• Evaluate emerging technologies and establish external partnerships to accelerate DARe’s AI capabilities.
• Translate scientific questions into computational strategies and select fit-for-purpose statistical, machine-learning, AI, and bioinformatics approaches.
• Build organizational connectivity to support 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.

Benefits

• Performance-based cash incentive.
• Depending on the level of the role, eligibility to be considered for annual equity awards.
• Health, life, and disability benefits for eligible US-based employees.
• 401(k) with company contribution and match.
• Vacation, personal days, holidays, and other leaves.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree