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 Qualifica