We are looking for a Data Scientist with expertise in machine learning, predictive modelling, and healthcare analytics to contribute to National Project ENTenna. This role involves developing AI models, optimizing algorithms for patient stratification, and integrating AI into real-world hospital workflows.
Key Responsibilities
Develop AI/ML Models: Build predictive algorithms for patient risk stratification and health outcome forecasting.
Analyse Large-Scale Healthcare Data: Work with EMR data, symptom scores, and clinical registries.
Implement AI-Driven Decision Support: Optimize pre-flight check-in systems and telehealth triage models.
Collaborate with Clinicians & Engineers: Translate clinical needs into data-driven solutions.
Ensure Data Compliance & Security: Work within PDPA, MOH AI Ethics, and HSA regulations.
Research & Publication: Contribute to peer-reviewed papers & grant applications.
Required Qualifications
Bachelor’s, Master’s, or PhD in Data Science, AI, Computer Science, Bioinformatics, or a related field.
Experience in Python, R, SQL, and machine learning frameworks (AWS and RAG).
Strong understanding of healthcare datasets (EMR, Health service research).
Hands-on experience with predictive modelling, NLP, or LLMs in healthcare.
Ability to communicate complex AI insights to non-technical stakeholders.
Preferred Qualifications
Experience working with healthcare AI models in clinical settings.
Familiarity with cloud platforms (AWS, Azure, or Google Cloud) for AI model deployment.
Knowledge of FHIR, HL7, and medical data (DICOM format).
Publication record in AI, predictive modelling, or digital health is a plus.