Data Analyst (DMOAT)

SingHealth Group; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

National Cancer Centre Singapore Pte Ltd is seeking a Data Analyst (DMOAT) to support research initiatives by managing, curating, and analyzing diverse clinical and genomic datasets. The role contributes to advancing patient care and translational research through data-driven insights.

You will work with clinicians, researchers, and regulatory stakeholders, building pipelines on AWS, maintaining data quality, and generating dashboards for grants and publications.

Qualifications

• Bachelor’s or Master’s degree in a relevant biomedical/health data field.
• Experience with clinical or healthcare datasets (EHRs, registries, trials, RWE).
• Familiarity with medical terminology and coding standards (ICD, SNOMED, LOINC).
• Strong analytical, problem-solving, and data interpretation skills.
• Ability to communicate complex findings to technical and clinical stakeholders.

Responsibilities

• Curate, clean, standardize, and integrate clinical, genomic, pathology, lab, registry, and trial datasets.
• Ensure data quality and governance; maintain data integrity and secure access.
• Link clinical and molecular datasets using standardized models; manage databases on AWS.
• Develop genomic analysis pipelines and automate QC procedures.
• Generate dashboards, reports, and analytics for projects, grants, and publications.
• Collaborate with clinicians, researchers, industry partners, and regulatory stakeholders.

Skills

Analytical thinking

Communication

Data visualization

Data mining

Education

Bachelor’s or Master’s degree in Biomedical Sciences/Public Health/Biostatistics/Bioinformatics/Data Science

Tools

AWS

OMOP CDM

Job description

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National Cancer Centre of Singapore Pte Ltd

Data Analyst (DMOAT)

Job Category: Research

The Data Specialist – Real-World Evidence (RWE) will support the research initiatives of the National Cancer Centre Singapore (NCCS) by managing, curating, and analyzing clinical data to generate actionable insights. The incumbent will be responsible for enhancing existing databases, ensuring data integrity, and integrating outputs with ongoing and future initiatives.

By translating complex clinical data into meaningful outputs, the role will directly contribute to advancing patient care, research excellence, and policy impact. The position also offers opportunities to engage with multi-stakeholder partners, including clinicians, researchers, industry, and regulatory bodies, to strengthen the role of real-world evidence in oncology.

Responsibilities

1.Data Integration & Governance

• Curate, clean, standardize, and integrate clinical, genomic, pathology, laboratory, registry, and trial datasets.
• Ensure data quality, consistency, completeness, and compliance with institutional data governance requirements.
• Link clinical and molecular datasets using standardized data models.
• Manage and maintain clinical and genomics databases hosted on AWS and institutional platforms.
• Monitor database performance, security, access controls, backup/recovery, and cost utilization.
• Ensure databases remain operational, scalable, and compliant with applicable policies.
• Develop, optimize, and maintain genomic analysis pipelines (AWS).
• Automate genomic data processing workflows and quality control procedures.
• Build federated data-sharing pipelines and support cross-institutional collaborations.
• Ensure interoperability with national and international data standards.
• Perform statistical analyses, data mining, and visualization of clinical and genomic datasets.
• Identify trends, biomarkers, patient outcomes, and research opportunities.
• Generate dashboards, reports, and analytical outputs for research projects, grants, and publications.

5.Research Collaboration & Stakeholder Engagement

• Support clinical investigators with study design, data extraction, and interpretation of results.
• Contribute to grant proposals, manuscripts, abstracts, and conference presentations.
• Collaborate with clinicians, researchers, industry partners, healthcare institutions, and regulatory stakeholders on data-driven initiatives.

Requirements:

• Bachelor’s or Master’s degree in Biomedical Sciences, Public Health, Biostatistics, Bioinformatics, Data Science, or a related discipline.
• Experience working with clinical or healthcare datasets (e.g., electronic health records, registries, clinical trials, real-world evidence, and observational studies).
• Familiarity with medical terminology and healthcare coding standards (e.g., ICD, SNOMED, LOINC).
• Strong analytical, problem-solving, and data interpretation skills.
• Ability to communicate complex analytical findings effectively to both technical and clinical stakeholders.
• Familiarity with the OMOP Common Data Model (CDM), including data mapping, terminology standardization, and healthcare database structuring, is advantageous.
• Experience in medical coding, terminology mapping, or healthcare data standardization is preferred.
• Strong attention to detail with commitment to data quality and accuracy.
• Collaborative mindset with ability to work across multidisciplinary teams.
• Adaptability and willingness to learn new tools, methodologies, and clinical domains.
• Motivation to contribute to translational research with potential impact on patient care.
• Interest in expanding into multi-stakeholder engagement, including collaborations with industry and regulatory agencies.