Data Analyst (DDOIT)

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.

Your responsibilities will include:
1) 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.
2) 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.
3) 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.
4) 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.