Assistant Director, Data Analytics (Statistical method)

Our client, a Singapore public-sector organisation focused on integrating health and social care services to better support the ageing population and community care needs.

The organisation works closely with hospitals, government agencies, and social service partners to ensure individuals receive appropriate care in the community, especially during care transitions after hospital discharge.

Role Overview

Lead advanced statistical analysis, quantitative modelling, and programme evaluation to support evidence-based policy and operational decision-making in the healthcare and community care sector.

Ensure all insights are derived from rigorous, defensible statistical methods and translate complex data into actionable decisions.

• Lead statistical modelling and advanced quantitative analysis (regression, hypothesis testing, causal inference)
• Drive programme evaluation design, including sampling, outcome definition, and study methodology
• Conduct and supervise analysis addressing small sample size, bias, and data limitations
• Ensure high-quality insights through statistical validation and robust analytical frameworks
• Develop BI outputs using statistical summaries, forecasting, and trend analysis
• Translate statistical findings into clear insights for policy and operational teams
• Guide stakeholders in framing business questions into testable statistical problems
• Mentor teams in applied statistics and quantitative methods
  
  
  Requirements
  
  
  
• Degree in Statistics, Mathematics, Data Science, Economics, or related field
• 10+ years of experience in applied statistics, analytics, or research, preferably healthcare/social sector
• 4+ years in a supervisory role
  
  Technical Skills
  
  
  
• Strong grounding in statistical methods (regression, inference, sampling, experimental design)
• Proficient in Python, R, or Stata
• Experience with Power BI or Tableau
• Strong understanding of data quality, validation, and statistical interpretation
  
  
  

Wilson Tay
Direct Line: 6697 7866
EA License No: 91C2918
Personnel Registration Number: R2091205