Research jobs in Singapore

The National Kidney Foundation (NKF) is dedicated to promoting kidney health and providing quality, highly subsidised dialysis treatment and holistic care to patients. We strive to be an advocate and integrator for the community, by the community.

While supporting kidney failure patients with quality dialysis and integrated care, NKF’s greater mission lies in preventing or delaying kidney failure through health education, deeper community integration, and strategic partnerships.

As we work toward our Future Forward 2030 vision, we remain committed to:

• Tackling the growing prevalence of kidney failure
• Enhancing patient support and care
• Leveraging technology to improve the efficacy and quality of treatment

We are seeking a skilled and driven Senior Data Analyst/Statistician to advance clinical and scientific decision-making through robust data management and advanced statistical analysis. This role offers the opportunity to lead data strategy development for dialysis services, translating complex insights into actionable recommendations that drive research, quality improvement, and operational excellence.

• Collect, clean, validate, and manage clinical datasets.
• Establish robust data management frameworks, SOPs, data validation protocols and quality assurance processes.
• Design and implement data collection tools such as case report forms.
• Manage and optimize clinical databases and electronic data capture (EDC) systems such as REDCap.
• Ensure data quality, integrity, security, access controls and compliance with ICH-GCP, HIPAA, GDPR, and other healthcare regulations.

• Provide statistical input in study design, including sample size calculation, randomization, and power analysis.
• Develop and execute statistical analysis for clinical research studies and quality improvement projects.
• Apply advanced statistical techniques (e.g., regression models, survival analysis, mixed models, Bayesian methods).
• Generate high-quality statistical reports, tables, listings, and figures for publications and presentations.

• Develop dashboards, KPIs, and outcome measures for clinical and operational performance.
• Conduct trend analysis, predictive analytics, and health economics evaluations.
• Build decision support tools and risk stratification models to enhance evidence-based practice.
• Provide executive-level reports for leadership, regulatory requirements and support in clinical audit processes.

• Use programming tools (R, Python, SQL, SAS, STATA) for analysis, automation, and algorithm development.
• Design automated workflows to streamline healthcare analytics and reporting.
• Evaluate and implement new analytical tools, visualization platforms, and solutions.
• Explore AI/ML applications and collaborate with IT on database design and system optimization.

• Bachelor’s, Master’s, or PhD in Statistics, Biostatistics, Epidemiology, Data Science, or related quantitative field.

• 5–7 years of experience in healthcare analytics or clinical research.
• Experience in nephrology, dialysis, or chronic kidney disease research is highly desirable.
• Familiarity with SQL, REDCap, and EDC platforms.
• Experience in machine learning, predictive modelling, and real-world evidence (RWE) analytics.
• Knowledge of health economics and outcomes research methodologies.
• Experience with real-world evidence studies and observational research.
• Exposure to large language models and natural language processing in healthcare applications.
• Proficient in R, SAS, SPSS, STATA, or Python.
• Skilled in regression modelling, survival analysis, and multivariate techniques.
• Experienced with data visualization tools (e.g., Tableau, Power BI).
• Knowledge of clinical data standards (HL7, FHIR) and regulatory frameworks.

• Demonstrates exceptional attention to detail and strong analytical thinking to solve complex problems effectively.
• Demonstrates an innovative mindset in developing creative solutions for challenging data and research scenarios.
• Collaborates effectively with cross-functional stakeholders in both clinical and research environments.
• Communicates complex statistical concepts clearly to non-technical audiences.
• Exhibits leadership and mentoring experience in guiding junior analysts or research staff.