Research Assistant - Data Research ($35-45k + bonus)

Responsibilities

• Design, develop, and maintain research-grade data pipelines and analytical workflows using Python, R, and SAS.
• Collect, clean, transform, validate, and integrate structured and unstructured datasets from multiple research sources.
• Conduct statistical analyses, exploratory data analyses, and quantitative research to generate insights and support scientific investigations.
• Collaborate closely with principal investigators, research scientists, postdoctoral researchers, and external academic partners on research projects.
• Develop reproducible research methodologies, analytical models, and data processing frameworks that meet academic and publication standards.
• Support experimental design, hypothesis testing, and interpretation of research findings.
• Prepare technical reports, research summaries, data visualizations, and documentation for internal stakeholders, publications, and presentations.
• Ensure data quality, integrity, governance, and compliance with relevant research and ethical standards.

Requirements

• Master's degree or MPhil (PhD preferred) in Data Science, Statistics, Biostatistics, Computer Science, Applied Mathematics, or a related quantitative discipline.
• 2 to 6 years of relevant experience in data research, quantitative analysis, or scientific research environments.
• Prior experience working in a university research laboratory, academic institution, research center, or equivalent research-driven environment is strongly preferred.
• Strong programming skills in Python, R, and SAS, with demonstrated experience developing analytical and statistical solutions.
• Solid foundation in statistics, experimental design, data modeling, and quantitative research methodologies.
• Hands-on experience with large-scale datasets, data wrangling, data quality validation, and data management
• Excellent written and verbal communication skills, with the ability to present technical findings to both technical and non-technical audiences.
• Demonstrated track record of working effectively in multidisciplinary and collaborative research teams.
• Communication skills in Cantonese and English.