AI-Driven Healthcare Analytics Lead

NHG Health; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

NHG Health is seeking a Senior Data Scientist to lead analytics initiatives across healthcare domains in Singapore. You will design and deploy ML models, build data pipelines, and partner with clinicians to drive measurable improvements in care pathways.

You will also develop dashboards and reports for non-technical stakeholders, ensuring data quality and robust validation of analytics in real-world settings.

Qualifications

• Master’s or PhD in a quantitative field such as CS, Math, Data Analytics, Data Science or Statistics.
• Formal training in data science, analytics, ML, or AI is required.

Responsibilities

• Design, develop, and implement advanced analytics and ML models to support clinical decision-making and care pathway optimisation.
• Build, maintain, and optimise automated data pipelines and ETL processes.
• Clean, preprocess, validate, and analyse large healthcare datasets for accuracy and completeness.
• Apply statistical methods and data mining to identify patterns and insights in healthcare data.
• Develop predictive models to support population health and primary care initiatives.
• Collaborate with clinical and operational teams to integrate AI solutions into care workflows.
• Create interactive dashboards and reports with usability for non-technical stakeholders.
• Monitor data quality and validate analytics solutions in real-world settings.

Skills

Python

R

SQL

Data visualization

Education

Master’s or PhD in quantitative discipline

Formal training in data science/analytics/ML/AI

Tools

Tableau

Power BI

AWS

Streamlit

NextJS

TypeScript

FastAPI

Job description

NHG Health is seeking a Senior Data Scientist to lead analytics initiatives across healthcare domains in Singapore. You will design and deploy ML models, build data pipelines, and partner with clinicians to drive measurable improvements in care pathways.

You will also develop dashboards and reports for non-technical stakeholders, ensuring data quality and robust validation of analytics in real-world settings.