Intern, Data Science & Public Health Analytics, ACE

Project title: Predictive Analytics and Digital Solutions for Migrant Worker Health Surveillance. The Public Health and Surveillance (PHS) team within MOM's Assurance Care and Engagement (ACE) division is responsible for monitoring the health status of dormitory-dwelling migrant workers and minimising infectious disease outbreaks during peacetime and pandemic situations. The data visualisation tools developed will facilitate evidence-based policy decisions by translating complex epidemiological data into clear, actionable insights for policymakers. These visualisations will enable rapid identification of emerging health threats, support timely policy responses, inform resource prioritisation across geographical areas, and provide transparent communication of health trends to stakeholders. By presenting data in intuitive formats, these tools strengthen the policy development cycle, from problem identification and policy formulation to implementation monitoring and impact evaluation. This internship offers a unique opportunity to support policy development through three-part data analytics projects that will transform PHS surveillance capabilities. The intern will develop: (1) a time series forecasting model to predict Acute Respiratory Infection cases, enabling proactive resource planning and early intervention protocols; (2) an interactive digital twin simulation platform modelling infectious disease transmission in dormitories and enabling policymakers to evaluate intervention strategies and optimise containment measures for pandemic preparedness; and (3) a geospatial dashboard supporting policy monitoring, targeted interventions, and assessment of policy effectiveness across Singapore's dormitory network. These projects directly support MOM's mission to safeguard migrant worker welfare through data-driven decision-making and align with whole-of-government priorities in public health policy, evidence-based governance, and pandemic preparedness planning.

Phase 1: Predictive Modelling of ARI Cases (Weeks 1-6) - Develop and tune a time series forecasting model for accurate prediction of ARI case volumes amongst dormitory-dwelling migrant workers - Validate model outputs against historical data and assess forecasting accuracy - Document model methodology and provide recommendations for operational implementation Phase 2: Development of Digital Twin Simulation of ID Spread (Weeks 7-11) - Develop an interactive simulation UI for infectious disease spread in dormitories - Incorporate user inputs including dormitory layout, common areas, occupancy density, and type of infectious disease - Adapt the SEIR (Susceptible-Exposed-Infectious-Recovered) epidemiological model into the simulation framework - Test various intervention scenarios and document findings Phase 3: Visualisation of ID Spread and Hotspots (Weeks 12-16) - Develop a comprehensive geospatial dashboard in Power BI showing infectious disease spread and hotspots involving migrant workers across dormitories - Integrate multiple data sources including health surveillance data and geospatial information using QGIS and Python - Create intuitive visualisations that support rapid decision-making and targeted interventions - Prepare user documentation and conduct knowledge transfer sessions Throughout the internship: - Work closely with PHS team members to understand domain requirements and operational needs - Present progress updates and findings to stakeholders - Ensure proper documentation for project continuity and future maintenance

Essential Skills: - Strong foundation in data science, statistics, or computer science - Proficiency in Python programming for data analysis and modelling - Experience with time series forecasting techniques and model development - Familiarity with data visualisation tools, particularly Power BI - Strong analytical and problem-solving capabilities - Ability to work independently and manage multiple project phases Desirable Skills: - Knowledge of simulation modelling and epidemiological models (e.g., SEIR model) - Experience with geospatial analysis tools such as QGIS - Understanding of public health concepts or infectious disease surveillance - UI/UX design experience for developing user-friendly interfaces - Experience with dashboard development and data integration - Ability to translate technical findings into policy-relevant insights Personal Attributes: - Strong communication skills to engage with stakeholders - Attention to detail and commitment to data quality - Ability to translate technical findings into actionable insights - Interest in applying data science to real-world public health challenges