Sr Asst Manager, Data Intelligence & AI

Tan Tock Seng Hospital; Singapore; On-site; SGD 110,000 - 170,000; Full time

Job summary

Tan Tock Seng Hospital in Singapore is seeking a Senior Data Analyst / AI Engineer to design, build, and operationalise AI-powered solutions with clinical domain experts and IT teams. You will focus on cloud-native engineering and scalable, production‑grade models to improve patient care and health services.

You will mentor junior data scientists, translate clinical needs into analytical solutions, develop data pipelines and MLOps workflows, and contribute to organisational data science strategy

Qualifications

• Degree or Master's in Data Science, Statistics, Computer Science, Computer Engineering, or equivalent with extensive data analysis experience.
• 3+ years of experience developing and implementing data science solutions in healthcare.
• Advanced skills in statistical modelling, machine learning, and deep learning with hands-on AI engineering, including model serving, containerisation, and CI/CD pipelines.
• Strong proficiency in cloud platforms and managed ML services such as SageMaker and Azure ML.
• Strong programming skills in Python and/or R.
• Hands-on experience with Simulations like FlexSim is a plus.
• Ability to design and execute complex experiments and manage large-scale data projects.
• Strong communication skills to liaise between technical and clinical teams.

Responsibilities

• Lead end-to-end development of AI solutions from data extraction to model deployment on cloud infrastructure (AWS/Azure/Private Cloud).
• Collaborate with clinicians, pharmacists, and healthcare professionals to translate domain requirements into analytical solutions.
• Drive adoption of model outputs into clinical workflows and review deployed models for relevance and performance.
• Identify opportunities to integrate AI capabilities across functions and contribute to a hospital-wide data science strategy.
• Perform simulation modelling and optimisation to support operational and clinical decisions.
• Promote analytic visibility through journals and conferences; seek collaborations and funding; conduct training.
• Mentor junior data scientists and analysts.
• Uphold compliance, risk management, and administrative duties; participate in organizational development and change initiatives.

Skills

Data science

Machine learning

Deep learning

AI engineering

Python/R

CI/CD pipelines

Communication

Education

Master's in Data Science/Statistics/CS

Tools

Docker

Kubernetes

SageMaker

Azure ML

Job description

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.

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.