Data Scientist (Geospatial Team)

About the Role We are seeking a Data Scientist to join its Geospatial Team to design, develop, and deploy machine learning solutions that support long-term infrastructure planning and geospatial analytics. You will contribute to the development of the Client's Spatial Modelling Engine, which forecasts future education demand using data such as housing growth, demographics, migration patterns, land-use plans, and accessibility. This role offers the opportunity to apply advanced machine learning and geospatial analytics to solve complex planning challenges with real-world impact. Key Responsibilities Requirements Analysis Collaborate with planners, analysts, and business stakeholders to understand long-term infrastructure and planning requirements. Translate business requirements into analytical and technical solutions. Conduct exploratory data analysis (EDA) to identify trends and generate insights. Recommend scalable and practical machine learning approaches. Machine Learning Solution Design Design end-to-end machine learning architectures for geospatial analytics and demand forecasting. Define data pipelines, feature engineering strategies, and model serving frameworks. Develop scalable, maintainable, and auditable ML solutions suitable for long-term planning applications. Machine Learning Development Develop, test, deploy, and maintain machine learning models in production. Build data pipelines integrating multiple data sources, including:Housing development dataDemographic dataMigration patternsLand-use plansAccessibility metrics Work closely with data engineers and platform teams to operationalise and monitor machine learning models. Geospatial Analytics & Model Optimisation Develop predictive and spatial models for education demand forecasting. Apply techniques such as:Spatial regressionTime-series forecastingAgent-based modellingDeep learning Evaluate, validate, and continuously improve model performance and forecasting accuracy. Requirements Minimum Qualifications Bachelor's Degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, or a related discipline. Minimum 3–5 years of hands-on experience in Data Science or Machine Learning. Proven experience delivering machine learning models in production environments. Required Technical Skills Programming & Data Science Python SQL scikit-learn PyTorch TensorFlow Machine Learning Feature engineering Data wrangling Model development Model evaluation Model deployment Model monitoring Forecasting Ensemble learning Deep learning Regularisation techniques Geospatial Technologies Experience with one or more of the following is preferred: GeoPandas QGIS ArcGIS PostGIS Geospatial analytics Cloud Technologies Experience with one or more cloud platforms: AWS Microsoft Azure Google Cloud Platform (GCP) Preferred Experience Candidates with experience in any of the following will have an advantage: Geospatial data analytics Demographic modelling Urban planning Public sector analytics Singapore planning datasets such as URA Master Plan or HDB housing data Soft Skills Strong analytical and problem-solving skills Excellent communication and presentation skills Ability to explain technical concepts to non-technical stakeholders Strong stakeholder management and collaboration skills Self-motivated with the ability to work independently and as part of a cross-functional team What We're Looking For The ideal candidate should have: 3–5 years of Data Science experience Strong Python and SQL programming skills Hands-on experience developing production machine learning solutions Knowledge of geospatial analytics and spatial modelling Experience with cloud-based machine learning platforms A passion for applying data science to solve complex infrastructure and planning challenges