• Full Time | Contract
• Executive
• Bachelor Degree | Masters
• Singapore | Closing On 04 Nov 2021

Contract ending 30 June 2025

About Us

Singapore Management University is a place where high-level professionalism blends together with a healthy informality. The 'family-like' atmosphere among the SMU community fosters a culture where employees work, plan, organise and play together – building a strong collegiality and morale within the university.

Our commitment to attract and retain talent is ongoing. We offer attractive benefits and welfare, competitive compensation packages, and generous professional development opportunities – all to meet the work-life needs of our staff. No wonder, then, that SMU continues to be given numerous awards and recognition for its human resource excellence.

Job Description

• This position is for Research on Successful Ageing (ROSA)
• Data cleaning, processing and publication of updated Singapore Life Panel (SLP) dataset conducted in STATA
• Update of SLP data documentation (e.g. data dictionaries, briefings for derived variables)
• Assist with literature reviews, and staying up-to-date with academic literature on the treatment of longitudinal data
• Improve quality of SLP dataset by way of construction of attrition weights, constructing new derived variables, and devising new publication of academic papers (either individually on statistics / data science, or co -authoring alongsideresearchers in economics / sociology / psychology)
• Contribution to research collaborations with government ministries and agencies
• Providing advice to researchers on the data that is available in the SLP and its proper treatment
• Quarterly preparation of descriptive summary statistics for sharing at research team meetings, distribution in newsletters, or for sharing with the media.

Qualifications

• Degree and/or Master’s in Statistics / Mathematics / Data Science is preferred
• Strong skills in data processing, analytics and modelling using Stata is essential 
• Experience with longitudinal datasets is desirable
• Detailed knowledge of Excel
• Additional proficiency in SPSS or R will be highly valued
• Good written and verbal communication skills are required
• Familiarity with published research in quantitative methods, particularly longitudinal panel data
• Publications based on these methods would be advantageous