Data Analyst (DMODT)

NATIONAL CANCER CENTRE OF SINGAPORE PTE LTD; Singapore; In loco; SGD 60.000 - 95.000; Tempo pieno

Descrizione del lavoro

The Data Specialist - Real-World Evidence (RWE) at NATIONAL CANCER CENTRE OF SINGAPORE PTE LTD will manage and curate clinical, genomic, and registry datasets to generate actionable insights for cancer research and patient care.

You will build and optimize data pipelines on AWS, ensure governance and data quality, and translate complex analyses into dashboards and reports for investigators, regulators, and multi-stakeholder partners.

Competenze

• 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., EHRs, registries, trials, real-world evidence).
• Familiarity with medical terminology and healthcare coding standards (ICD, SNOMED, LOINC).
• Strong analytical, problem-solving, and data interpretation skills.
• Ability to communicate complex analyses to technical and clinical stakeholders.

Mansioni

• Data integration, curation, and governance of clinical, genomic, pathology, and registry datasets.
• Manage and optimize AWS-hosted databases; ensure security, access controls, and backups.
• Develop, optimize, and maintain genomic analysis pipelines (AWS) and data-sharing workflows.
• Perform statistical analyses, data mining, and visualization to identify trends and biomarkers.
• Collaborate with clinicians, researchers, industry partners, and regulators on data-driven initiatives.

Conoscenze

Analytical thinking

Data interpretation

Communication

Collaborative

Adaptability

Formazione

Biomedical Sciences / Public Health / Biostatistics / Bioinformatics / Data Science

Strumenti

AWS Cloud

OMOP CDM

SQL

Python

R

Descrizione del lavoro

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. 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.
2. 2.Database & AWS Cloud Infrastructure Management
   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.
3. 3.Genomics Pipeline Development & Data Sharing
   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.
4. 4.Data Analytics & Visualization
   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. 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.