Data Scientist (Geospatial Team)
Skills
About the role
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
Questions about this role
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