Sr Asst Manager, Data Intelligence & AI

Family Group: Administration

Job Summary

The Senior Data Analyst / AI Engineer will work closely with clinical domain experts, stakeholders, and IT teams within the Division of Informatics & Data (DID) to design, build, and operationalise AI-powered solutions, to perform simulation modelling and solve optimisation problems. This role bridges the gap between hands-on model development and strategic solution architecture, with a strong emphasis on cloud-native AI engineering and the deployment of scalable, production-grade models to improve patient care and health services delivery.

Main Duties and Responsibilities

Lead the end-to-end development of AI solutions - from data extraction, cleaning, and preprocessing through to model training, evaluation, and deployment on cloud infrastructure (e.g., AWS, Azure, or Hospital Private Cloud). This includes designing and implementing cloud-native data pipelines and MLOps workflows to ensure models are reliably versioned, monitored, and maintained in production environments.

Work closely with clinicians, pharmacists, and other healthcare professionals, to translate domain requirements into analytical solutions, drive adoption of model outputs into clinical workflows, and conduct regular reviews of deployed models to ensure continued relevance and performance.

Identify opportunities to integrate AI capabilities across functions and contributing to the development of a coherent, institution-wide data science strategy.

Able to perform simulation modelling and solve optimisation problems, applying techniques such as discrete-event simulation, linear/integer programming, or metaheuristic methods to support operational and clinical decision-making.

To increase the visibility of analytic work through journal publications and conference presentations, seek research collaborations and funding, and conduct training and knowledge-sharing sessions on AI, cloud computing, and analytics.

Mentor of junior data scientists and analysts is a key part of the role.

General compliance, risk management, and administrative responsibilities apply as required.

Participate actively in organisational development and quality improvement, act as a change agent at both hospital-wide and departmental levels, and be able to work beyond routine office hours during exigencies such as infectious disease outbreaks.

Job Requirements

Degree or Master's in Data Science, Statistics, Computer Science, Computer Engineering, or equivalent disciplines with extensive use of data for analysis is required.

A minimum of 3 years of experience in the development and implementation of data science solutions in a healthcare setting is expected.

Advanced skills in statistical modelling, machine learning, and deep learning, complemented by hands-on experience in AI engineering - including model serving, containerisation (e.g., Docker, Kubernetes), and CI/CD pipelines.

Strong proficiency in cloud platforms, including experience with managed ML services such as SageMaker, Azure ML, etc.

Strong programming skills in Python and/or R

Hands-on experience with FlexSim simulation software will be value-added

Ability to design and execute complex experiments, manage large-scale data projects, and think strategically about solution architecture is expected.

Strong communication skills to liaise between technical and clinical teams are essential.