Senior Analyst / Associate Principal Analyst, Data Science, Health Services Research Centre (2-year

Join SingHealth's Health Services Research Centre (HSRC), where cutting-edge data science meets real-world impact. HSRC supports health services research across SingHealth with expertise in data management, data science, health systems modelling, real world evidence, and implementation science. If you are passionate about using data to transform healthcare, this is your opportunity to contribute to research that shapes how care is delivered across Singapore's largest public healthcare cluster.

What You Will Do:

You will support advanced health services research and data science projects to improve healthcare outcomes, enhance operational efficiency, and support evidence-based decision-making. Your key responsibilities will include working closely with the data management team and key stakeholders to develop data mining capabilities to support the growth of SingHealth’s health services research programmes. You will collaborate with relevant clinical decision makers, health policy makers and hospital management to develop accurate harmonisation of clinical/operational databases to derive actionable insights for improving patient outcomes. You will also maintain project and database-specific data dictionaries and documentation, contribute to the drafting of scientific abstracts and manuscripts, and supervise and train junior analysts and interns.

You will also collaborate with health services research and analytics professionals to develop new project proposals and reports/manuscripts for the expansion of the research analytics role in SingHealth.

Job Requirements:

• Bachelor’s/Master’s/PhD in Business Analytics, Industrial Engineering, Statistics, Computer Science, Health Service Research, or related fields
• At least 3 years of working experience in data science or analytics, preferably in health services research
• Experience in predictive analytics, modelling & business intelligence (BI) with high performance computing techniques based on commercial statistical software (e.g. SPSS, Stata), open-source platforms (e.g. R, Python) and commercial BI tools (e.g. PowerBI, Tableau, OBIEE)
• Strong background in biostatistics, analytics, simulation and optimisation areas, with the ability to prioritise analytical approaches that deliver significant and measurable impact
• Team player with excellent communication and interpersonal skills
• Organised and meticulous, with the ability to work independently