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Develop predictive models and AI/ML solutions to improve patient care and hospital operational efficiency. Lead data-driven strategic initiatives and maintain data governance standards to support management decision-making.
Requires a STEM degree and at least 2 years of relevant experience in data science and AI. Proficiency in Python, R, SQL, and various AI/ML frameworks and automation tools is essential.
We are seeking a highly motivated individual with a strong foundation in statistics, data management, and Artificial Intelligence (AI)-related technical competencies to contribute meaningfully to patient care and hospital operational excellence.
In this dynamic role, you will work extensively with complex healthcare datasets, employing advanced statistical methodologies and machine learning techniques to surface insights that drive impact. You will design and develop predictive models and AI/ Machine Learning (ML)/Deep Learning solutions to support clinical and operational needs, alongside implementing automation to enhance workflow efficiency.
Beyond analytics, you will lead and coordinate data-driven and digital strategic initiatives, uphold data quality and governance standards, and translate insights into actionable recommendations that support management decision-making. You will also identify opportunities for process improvement to advance patient care delivery, collaborating closely with internal and external stakeholders in a fast-paced and innovation-driven environment.
Requirements :
SingHealth drives the transformation of healthcare and provides affordable, accessible, quality healthcare. With over 40 clinical specialties, a network of acute hospitals, national specialty centres, polyclinics and community hospitals, it delivers comprehensive, multidisciplinary and integrated care. As part of the SingHealth Duke-NUS Academic Medical Centre, SingHealth works with Duke-NUS Medical School to advance medical research and education to improve patient care.
Offices: 10 Hospital Boulevard, Bukit Merah, 168582, SG
