Research Assistant - Health Economics & Data Analytics

National University of Singapore; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

The National University of Singapore's Lien Centre for Palliative Care at Duke-NUS Medical School is seeking a research-focused professional to advance quantitative health research. The role involves designing studies, analyzing large health datasets, and applying econometric methods to inform policy and practice.

You will contribute to manuscripts for high-impact journals and assist with grant reporting while collaborating with clinicians, data scientists, and policy stakeholders on impactful

Qualifications

• Bachelor's or master's degree in a quantitative field (econ/stats/public health).
• Strong knowledge of econometric analysis.
• Proficient in R, Stata, or SAS.
• Experience working with large datasets.
• Strong analytical, writing, and communication skills.
• Ability to work independently and in a team.

Responsibilities

• Plan, organize and conduct research studies under PI supervision.
• Perform advanced quantitative analyses on large datasets.
• Apply econometric and statistical methods to evaluate health policy.
• Contribute to manuscript preparation for high-impact journals.
• Support grant preparation, reporting, and coordination.
• Collaborate with clinicians, data scientists, and policymakers.

Skills

Statistical analysis

Econometrics

Data analysis

Communication skills

Education

Bachelor's /Masters' Degree in Economics, Statistics, Public Health or related quantitative field

Tools

R

Stata

SAS

Job description

The National University of Singapore's Lien Centre for Palliative Care at Duke-NUS Medical School is seeking a research-focused professional to advance quantitative health research. The role involves designing studies, analyzing large health datasets, and applying econometric methods to inform policy and practice.

You will contribute to manuscripts for high-impact journals and assist with grant reporting while collaborating with clinicians, data scientists, and policy stakeholders on impactful