Director, AI and Machine Learning for Biology

Description

The company is building an AI-driven discovery engine that combines longitudinal human data, genetics, multi-omics, imaging and advanced biological models to find the causes of aging, resilience and regeneration, then turns those findings into new therapeutic targets and medicines for age-related disease.

This director role sets the global data science and AI direction and builds the US group in San Diego. You will pair strategy with hands-on technical depth, link computational and experimental work, and turn new methods into drug discovery decisions.

Internal job title: Director Data Science.

Responsibilities

• Lead the US data science and AI group and set the global AI and machine learning direction.
• Set a ranked portfolio of data science and AI initiatives, define how scientific and operational impact will be measured, and make sure the work leads to better target choices, sharper experiment design and faster discovery.
• Help shape and run AI work for target identification, prioritization and validation across disease programs, and contribute to the long-term scientific AI vision.
• Lead the building and use of biological foundation models, multimodal learning, biomedical knowledge graphs and agentic workflows for evidence integration and target ranking.
• Work across human genetics, longitudinal clinical trajectories, proteomics, transcriptomics, metabolomics, imaging and electronic health records.
• Hire, lead and grow a high-performing US team in applied AI, machine learning, computational biology and data science, with real development paths for early-career staff.
• Scout emerging technologies and set up external partnerships to advance AI capability.
• Turn scientific questions into computational plans, choosing suitable statistical, machine learning, AI and bioinformatics methods.
• Build connections across the organisation so teams collaborate, share knowledge and work as one team across locations and disciplines.
• Drive AI adoption across the department.
• Work closely with Data and Digital, Discovery Sciences and disease areas.

Requirements

• PhD in machine learning, computational biology, data science, computer science, systems biology or a related quantitative field, plus a deep understanding of biology.
• 10+ years applying advanced computational and AI methods to biomedical research, drug discovery or translational medicine.
• Proven track record leading global, multidisciplinary teams across AI, human data and experimental science.
• Experience developing or applying advanced machine learning 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 modelling.
• Strong experience with large-scale model training, distributed computing, model adaptation and deployment within MLOps frameworks.
• Strong coding skills in Python and deep learning frameworks, plus experience with version control systems.
• Experience with omics data (transcriptomics, proteomics, metabolomics) and cellular imaging data.
• Ability to lead and influence across matrix organisations, with excellent communication and stakeholder management skills.
• Proven ability to work effectively in a fast-paced, highly collaborative research environment.
• Desirable: expertise in statistical genetics, including genome-wide association studies, rare variants, Mendelian randomization, colocalization or fine-mapping.
• Desirable: understanding of modern data foundations, including ETL/ELT pipelines, biomedical ontologies, metadata standards, data governance and FAIR data principles.
• Desirable: expertise in diseases of aging, neurodegeneration, cardiometabolic disease, regeneration biology or related therapeutic areas.
• Desirable: experience with knowledge graph technologies and scientific knowledge integration platforms.
• Desirable: experience developing biological aging clocks.
• Skills listed for the role: artificial intelligence, business value creation, change management, a curious mindset, data governance, data literacy, data quality, data science, data visualization, deep learning, learning agility, machine learning, machine learning algorithms, mentorship, stakeholder engagement, statistical analysis and time series analysis.

Conditions

Based onsite in San Diego, California.

Base salary range is $194,600 to $361,400 per year. The final offer depends on factors such as skills and experience, and pay is reviewed periodically after joining. The company may change the published range based on company and market factors.

Eligible for a performance-based cash incentive and, depending on level, possible annual equity awards.

Benefits

• US-based eligible employees receive health, life and disability coverage, a 401(k) with company contribution and match, and other benefits.
• Generous time off, including vacation, personal days, holidays and other leaves.