Overview
Reporting to the Deputy Group Chief Technology Officer, you will propose, develop, and implement advanced Artificial Intelligence / machine learning models and pipelines to augment clinical workflows in NUHS cluster. The candidate will also ensure the adequacy and effectiveness of the models and tools for NUHS.
Responsibilities
- Develop and oversee efficient data collection pipelines across NUHs as well as the institutes we collaborate and work with.
- Ensure data governance, security compliance (PDPA / HIPAA / GDPR / etc.), and interoperability for seamless integration.
- Work with NUHS IT and clinical teams to automate data extraction and structuring from medical records, imaging systems, and wearable devices
- Lead the implementation of AI-driven predictive models for clinical decision support and operational efficiencies.
- Establish frameworks for model validation, ensuring AI tools are generalizable, bias-free, and clinically relevant.
- Collaborate with data scientists, clinicians, and regulatory bodies to refine AI applications. Design intuitive user interfaces to facilitate AI adoption by clinicians and hospital administrators.
- Ensure seamless real-time integration of predictive analytics into Electronic Medical Records (EMRs), dashboards, and reporting tools.
- Work with human factors specialists to optimize workflow efficiency and user engagement. Oversee scalable AI deployment across different institutions, ensuring reliability and minimal downtime.
- Implement APIs and middleware solutions for seamless interoperability between clusters.
- Drive cross-cluster alignment by ensuring standardization in AI outputs, reporting formats, and data-sharing agreements. Engage with executive leadership, healthcare providers, data scientists, and engineers to drive AI-enabled transformation.
- Guide junior data scientists in the AIO team, troubleshoot problems so as to achieve end goal.
- Organising our local AI conferences, showcase NUHS AI capabilities to attract further talents.
- Develop strategic roadmaps for AI expansion, keeping in mind emerging technologies and regulatory requirements.
Requirements
Master’s or Ph.D. in Data Science, Computer Science, Biomedical Engineering, Bioinformatics, or a related field.Prepare technical documentation, research papers, and presentations for stakeholders.Strong expertise in Python, R, SQL, and libraries such as TensorFlow, PyTorch, Scikit-learn.Experience with healthcare data standards (FHIR, HL7, DICOM).Hands-on experience in deep learning, computer vision, NLP, and time-series analysis.Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps tools for deploying models.Strong knowledge of biostatistics, epidemiology, and clinical research methodologies.Experience in working with large-scale medical datasets and electronic health records.Understanding of AI ethics, bias mitigation, and interpretability in healthcare AI.Excellent communication skills to collaborate with clinicians, engineers, and business stakeholders.Work as a team member to fulfill requirements and tasks assigned by the Reporting Officer.#J-18808-Ljbffr