What you will be working on

As part of the team, you will play a key role in managing and enhancing the data quality of the Retirement and Health Study (RHS), a large-scale longitudinal survey with approximately 20,000 respondents across multiple waves. You will contribute to areas including questionnaire design, data processing, academic collaboration, and data science initiatives to support evidence-based policymaking.

You will undertake the full data quality assurance pipeline — developing validation rules, managing data imputation, and integrating administrative and survey data using tools such as Stata and Python. You will also review and improve the RHS questionnaire from a data quality perspective, ensuring it remains robust, relevant, and well-suited for longitudinal analysis.

Beyond data operations, you will manage academic collaborations with local universities and government agencies, assessing research proposals and reviewing drafts to ensure alignment with data governance requirements and policy objectives. You will also undertake data science and digital initiatives, including building models and automation tools to improve data quality and respondent engagement.

In this role, you will:

• Undertake comprehensive data quality assurance activities, implementing quality control measures throughout the data lifecycle to ensure the accuracy, completeness, and integrity of datasets.
• Undertake the organisation, storage, and retrieval of datasets, and maintain detailed documentation of data quality processes and methodologies to ensure transparency and replicability.
• Collaborate with cross-functional teams, survey companies, academic institutions, and government agencies to coordinate study planning and execution, and facilitate seamless data sharing as part of these collaborative efforts.
• Contribute to data science projects aimed at enhancing data quality or supporting the execution of the study.
• Identify opportunities to improve data management processes, proposing and implementing enhancements where appropriate.

What are we looking for

We value the diverse talents and experiences that each individual brings to the table. While mastery of every requirement may not be necessary, familiarity and expertise in some of the following areas will position you for success within this team.

• Relevant experience in statistical data processing, data management, or a related field, with familiarity in survey methodology being an advantage.
• Experience in programming tools such as Stata, Python, or R for data processing and analysis.
• Experience with machine learning or data science applications is an advantage.
• Ability to work across multiple stakeholders — from survey companies and researchers to policy owners — and translate complex requirements into practical solutions.
• Communicates effectively, both in writing and speaking.
• Works independently and manages priorities effectively.
• Adaptable and resourceful in handling different tasks and challenges.

To support Whole-of-Government statistical capabilities and provide diverse opportunities for our officers, Singapore Department of Statistics (DOS) recruits for statistical roles across the Public Service. For this role in Central Provident Fund Board (CPFB), successful candidates will be employed by DOS and seconded to CPFB. Successful candidates may also explore other career opportunities in DOS and other public agencies after their stint with CPFB. Further details will be shared with shortlisted candidates.