Sr Asst Manager, Data Intelligence & AI

NHG Health; Singapore; On-site; SGD 100,000 - 150,000; Full time

Job summary

NHG Health is seeking a Senior Data Analyst / AI Engineer to design, build, and operationalise AI-powered solutions in the Division of Informatics & Data. You will bridge hands-on model development with production-grade architecture on cloud platforms.

Responsibilities include end-to-end AI project delivery, collaboration with clinicians and IT, simulation modelling, and mentoring junior data scientists.

Qualifications

• Degree or Master's in Data Science, Statistics, CS, or CS Engineering, with extensive data-analysis experience.
• At least 3 years of healthcare data science experience.
• Hands-on AI engineering experience: model serving, containerization, and CI/CD.
• Strong communication to liaise with clinical teams.

Responsibilities

• Lead end-to-end development of AI solutions from data prep to model deployment on cloud infrastructure.
• Collaborate with clinicians and IT to translate requirements into analytical products.
• Develop scalable data pipelines and MLOps workflows for production models.
• Perform simulation modelling and solve optimisation problems for decision making.
• Publish findings and seek research collaborations and funding opportunities.
• Mentor junior data scientists and analysts.
• Support organisational development, quality improvement, and crisis response as needed.

Skills

Python and/or R

Statistical modelling

Machine learning / deep learning

Cloud-native AI engineering

Communication skills

Mentoring

Project planning

Education

Bachelor's or Master's in Data Science / Statistics / Computer Science / Computer Engineering

Tools

Docker

Kubernetes

CI/CD pipelines

SageMaker

Azure ML

Job description

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.