Data Coder (Assistant Manager), NUHS Education & Research Office (2 Years Contract)

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 or Diploma in disciplines related to Computer Science, Data Science, Software Engineering, Business Analytics, Biomedical Engineering, Bioinformatics, or a related field will be an advantage.

• Min 3 years of experience on below:

• Understanding of machine learning models and algorithms and their applications, particularly in the healthcare domain

• 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