Statistical Specialist (Data Analytics and Methodology), Data Collection, MRSD

The position is located in the Manpower Research and Statistics Department (MRSD), Singapore. The department produces a wide range of national labour market statistics to facilitate informed decision-making within the government and the community-at-large. The main role of the position is to collect, analyse and interpret data using innovative tools, methods and approaches to optimise survey operations and facilitate policy making and development. • Leveraging on a variety of data sources (i.e survey data, administrative data), including big data to generate actionable insights. • Apply statistical techniques and data mining methods to identify patterns and trends, employment patterns, and labour market dynamics. • Designing user-friendly data visualization dashboards, presentation slides, charts and tables. • Undertake both qualitative and quantitative research and analysis, including predictive modelling, time-series forecasting. Commission research, draft terms of reference for research consultants and monitor and coordinate their work. • Draft and/or provide technical input into the development, peer review and editing of occupational/industry classification system reviews, working papers, reports, publications and other knowledge products and contribute to their dissemination. • Keeping up to date with advancements and developments in machine learning so as to leverage new tools and techniques. • Provide evidence-based technical content for social media, digital and other knowledge-sharing tools and platforms, with a view to reaching broad and diverse audiences. • Developing and implementing policies related to data governance policies, procedures and standards, including identifying and resolving data quality issues. • Perform other relevant duties as assigned. • Tertiary qualifications with a preferred field of study in Economics, Statistics, Mathematics, Computer Science or other relevant field. • Experience in research and quantitative analysis. Candidates with coding and programming experience (e.g. Python, R) will be considered favourably. • Good knowledge and understanding of theories, trends and approaches in the area(s) of machine learning/deep learning, natural language processing, large language modelling and econometrics modelling. • Good research and analytical skills. • Good communication, presentation and writing skills. • Ability to maintain effective and collaborative working relationships with key stakeholders.