Typical Accountabilities

Major responsibilities 
•    Apply and adapt large-scale foundation models (such as transformer-based architectures and pretrained multi-modal models) for biomedical research, including knowledge extraction, prediction tasks, and generative modelling.
•    Design, finetune, and validate machine learning algorithms—including foundation models—tailored to biological, multi-omics, and clinical datasets relevant to drug development. 
•    Create and implement novel computational algorithms to address challenges in disease biology, biomarker identification, patient stratification, and therapeutic response prediction.
•    Collaborate closely with bioinformatics experts and therapeutic area scientists to harmonize and integrate diverse multi-modal datasets—including genomics, proteomics, clinical, and imaging data—and apply advanced AI-driven methodologies to enable impactful translational research initiatives.
•    Present and explain analytic findings and model outputs to cross-functional teams, translating complex results into actionable recommendations.
•    Act as an AI advocate across multidisciplinary teams; promote understanding, adoption, and best practices for AI and machine learning methods in drug research, and mentor colleagues on leveraging advanced analytics for scientific discovery.
•    Champion reproducible research, code documentation, and ethical data science practices in sensitive research environments.

Education, Qualifications, Skills and Experience
•    PhD or MSc in Data Science, Computer Science, Biomedical Engineering, Bioinformatics, Applied Mathematics, or related field.
•    Hands-on experience developing, adapting, and finetuning foundation models (such as transformer architectures, large language models, and pretrained multi-modal models) for biomedical or healthcare applications.
•    Proficiency in model building, machine learning (including deep learning), algorithm development, and large-scale data processing in Python, R, or equivalent languages.
•    Minimum of 5 years of hands-on experience in data science, bioinformatics, or a related field, with a strong track record of delivering impactful results in a pharmaceutical or healthcare context.
•    Experience of addressing data compliance & localisation challenges with China data compliance right (e.g., CBDT, CSL) in the data platform related project is a strong plus.  
•    Agile experience is a plus.