Data Analytics & Insights (DAI) team under Group Care Plan Ops will support and work in close partnership with NUHS senior management, Group Specialty Chiefs (GSCs), Management Decision Support (MDS) teams and other stakeholders to realise the delivery of One Specialty, Multiple Sites and a OneNUHS patient care philosophy. The DAI team will develop innovative analytics solutions and derive actionable insights to support management decision making towards attainment of the healthcare vision and key priorities.
Responsibilities
- Identify data and information needs required to enable the vision and key priorities of the organisation.
- Collaborate with stakeholders to identify available and relevant datasets and make strategic recommendations on such collection, integration and usage.
- Develop, maintain and refine interactive dashboards using data visualisation tools such as Tableau.
- To assist in developing the timeline that will enable DAI to progressively meet stakeholder needs.
- Establish and prioritise dashboard and scorecard of key stakeholders and working collaboratively with Group Clinical Ops and Group Service Ops, to refresh the Dashboard and Scorecards on an ongoing basis.
- To be well versed with and keep updated on Epic and other operational applications in order to propose solutions that will address group operations management and senior management needs on operational excellence.
Requirements
- Bachelor’s Degree in Computer Science, Information Management, Mathematics, Statistics, Operations Research, Engineering or related disciplines with strong statistical modelling and machine learning skills.
- At least 3 years of relevant working experience with analytics tools e.g. SQL, Python, MS Excel (advanced), data visualisation tools (e.g. Tableau)
- Familiarity with healthcare setting is a plus.
- Fresh graduates with excellent data capabilities will be considered.
- Excellent interpxersonal skills, attention to detail, and flexibility to collaborate across various team areas and functions.
- Possess can-do attitude and work independently in ambiguous situations.
- Strong analytical and problem-solving skills
- Proficient in extracting, cleansing, and interpreting complex data with attention to detail and accuracy.
- Able to communicate sophisticated data science concepts clearly through concise reports and presentations, effectively conveying observations and recommendations.
