Senior Data AI Engineer – Cloud-Native Health Analytics

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

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.