Data Analyst (DDOIT)

NATIONAL CANCER CENTRE OF SINGAPORE PTE LTD; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

National Cancer Centre Singapore is seeking a Data Analyst to support population health and health economics research projects. The role involves working with large-scale healthcare and administrative datasets, including EMR and research cohort data, and collaborating with clinicians, health economists, and data science teams.

The candidate will perform data management, descriptive and inferential analyses, and contribute to manuscripts, reports, and grant submissions while adhering to data

Qualifications

• Bachelor or Master degree in Data Science, Statistics, Biostatistics, Public Health, Epidemiology, Health Economics, Computer Science, or a related field.
• Strong data wrangling and analytical skills using R, Python, STATA.
• Experience working with large, complex datasets in healthcare.
• Familiarity with EMR, registry, administrative, or research cohort data.
• Experience with survival analysis, regression modelling, and data visualization.

Responsibilities

• Data management, wrangling, harmonisation and linking of large healthcare datasets.
• Develop reproducible analytical workflows and data pipelines.
• Conduct descriptive and inferential analyses including survival and regression modelling.
• Create high-quality tables and figures for manuscripts, reports and grant submissions.

Skills

Data wrangling

R

Python

STATA

Survival analysis

Regression modelling

Data visualization

Large datasets

Education

Bachelor's or Master's degree in Data Science / Statistics / Biostatistics / Public Health / Epidemiology / Health Economics / Computer Science

Job description

We are seeking a Data Analyst to support various population health and health economics research initiatives at the National Cancer Centre Singapore. The successful candidate will work extensively with large-scale, linked administrative, clinical and research datasets, including electronic medical records (EMR), health and socio-demographic information collected through research studies and institutional/government administrative databases. This role sits at the intersection of oncology, health economics, epidemiology, and public health, and involves close collaboration with clinicians, health economists, epidemiologists, and data science teams across institutions.

Responsibilities

• Data Management & Wrangling:
  • Access, extract, clean, and manage large-scale healthcare and administrative datasets.
  • Harmonise and link data from multiple sources.
  • Develop reproducible data pipelines and well-documented analytical workflows.
  • Perform data quality checks, validation, and sensitivity analyses.
• Statistical Analysis & Modelling:
  • Conduct descriptive and inferential analyses to support:
  • Cancer incidence, outcomes and survival studies,
  • Healthcare utilisation and cost analyses,
  • Health economic evaluations and
  • Support advanced modelling as required, including regression modelling, survival analysis, and longitudinal analyses.
• Communication of analytical outputs:
  • Generate high-quality tables, figures, and summary outputs for manuscripts, reports, policy briefs and grant submissions.
  • Meet agreed milestones and deadlines for project deliverables.
• Data Governance, Compliance & Best Practices:
  • Adhere strictly to data security, privacy, and governance requirements when working with sensitive health data.
  • Maintain clear documentation and version control for all analytical work.
  • Support audits or reviews related to data access and analysis, where required.

Requirements

• Bachelor or Master degree in Data Science, Statistics, Biostatistics, Public Health, Epidemiology, Health Economics, Computer Science, or a related field.
• Strong data wrangling and analytical skills using one or more of the following - R, Python, STATA.
• Experience working with large, complex datasets, especially in healthcare setting.
• Familiarity with healthcare or clinical or biomedical research data structures (e.g. EMR, registry, administrative, research cohort data).
• Experience with statistical analysis especially survival analysis and regression modelling, and data visualisation.
• Experience in cancer-related research, health economics, or public health is highly desirable.
• Meticulous, with excellent organizational and time management skills.
• Good communication, organizational and interpersonal skills.
• Ability to complete tasks independently with minimal supervision.
• Ability to work on multiple projects involving multiple stakeholders concurrently.