Research Associate, Data Science, CREA
- Employer
- SINGAPORE MANAGEMENT UNIVERSITY
- Location
- Singapore
- Closing date
- 13 Jun 2020
View more
- Academic Discipline
- Mathematics & Statistics, Physical Sciences
- Job Type
- Research Related, Research Associate
- Contract Type
- Fixed Term
- Hours
- Full Time
5-year contract
- Contract
- Manager
- Masters
- Singapore
- Closing On 13 Jun 2020
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 Centre for Research on the Economics of Ageing (CREA)
- 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
- Providing advice to researchers on the data that is available in the SLP and its proper treatment
- Publication of academic papers (either individually on statistics / data science, or co-authoring as the data scientist alongside researchers in economics / sociology / psychology)
- Quarterly preparation of descriptive summary statistics for sharing at research team meetings, distribution in newsletters, or for sharing with the media
- Contribution to research collaborations with government ministries and agencies
- Improve quality of SLP dataset by way of construction of attrition weights, constructing new derived variables
Qualifications
- Master’s degree is preferred in Data Science / Statistics / Mathematics
- Candidates should strong knowledge of data processing in STATA
- Experienced knowledge of Excel 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
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