This role exists to empower the Research and Education Office to leverage data more effectively, supporting NUHS's mission to advance health through innovation, education, and translational excellence.
Responsibilities
- Support data-driven projects aligned with clinical and business goals
- Assist with engagement and collaboration with stakeholders
- Support the development of Proof of Concept and Proof of Value initiatives, and drive the scaling of solutions whether through hands-on implementation or by managing external vendors or partners
- Own and manage the end-to-end process from gathering and translating user and business requirements to ensure the delivery of impactful user-centre and data-centre outcomes
- Coordinate cross-function collaboration to align on goals, resources, timelines, success metrics
- Contribute to the operations and growth of the Data Insight Unit (DIU)
- Support day-to-day team operations to ensure smooth and efficient execution
- Capture and document best practices and lessons learned to promote knowledge sharing and team consistency
- Actively contribute to internal improvement initiatives aimed at enhancing team collaboration
- Participate in efforts to build long-term sustainability of team
Requirements
- Bachelor's degree in disciplines related to Computer Science, Data Science, Software Engineering, Business Analytics, Biomedical Engineering, Bioinformatics, or a related field will be an advantage.
- At least 4 years of experience in related roles.
- General understanding of machine learning models and algorithms and their applications, particularly in the healthcare domain
- General understanding of full-stack web development and the ability to quickly prototype proof-of-concepts.
- General proficiency in Python and SQL, with hands-on experience in frameworks such as PyTorch and Scikit-learn, plus anything else you can bring to the table
- Familiarity with cloud platforms and experience using MLOps tools for scalable and robust deployments
- Understanding of medical datasets, electronic health records, healthcare data standards
- Understanding of ethical considerations in AI including bias mitigation, model fairness and explainability, particularly in the healthcare context
- Excellent communication skills for cross-functional collaborations with clinicians, technical team, and business stakeholders
- Ability to prepare clear, concise technical documentation and presentation materials to effectively communicate ideas and outcomes to stakeholders
