SINGAPORE MANAGEMENT UNIVERSITY

Research Associate, Data Science, ROSA

Location
Singapore
Posted
16 Oct 2020
End of advertisement period
14 Nov 2020
Contract Type
Fixed Term
Hours
Full Time
  • Contract
  • Manager
  • Masters
  • Singapore | Closing On 14 Nov 2020

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 Centre 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 and constructing new derived variables.
  • Publication of academic papers (either individually on statistics / data science or co-authoring as the data scientist alongside researchers 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

  • Master’s degree is preferred in Data Science / Statistics / Mathematics.
  • 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.

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