Geospatial Data Scientist

You’ll be working as part of a newly formed data science team, focusing on spatial analytics and multi-sensor data fusion.

This role sits at the intersection of machine learning, geospatial data, and mathematical modelling, with a strong emphasis on solving real-world problems.

What You’ll Be Doing

• Developing algorithms for spatial data correlation and fusion
• Analysing and integrating multi-sensor datasets (radar, LiDAR, RF, imagery, etc.)
• Building machine learning models for classification, regression, and tracking
• Applying statistical techniques to quantify uncertainty and improve predictions
• Performing feature engineering and dimensionality reduction on spatial data
• Building tools to visualise and validate model outputs
• Working closely with engineers to deploy models into production systems

• Strong background in geospatial / spatial data science
• Experience working with Python and geospatial libraries (GeoPandas, GDAL, Rasterio etc.)
• Solid understanding of machine learning and statistical modelling
• Experience working with complex or large-scale datasets
• Ability to work in a cross-functional engineering environment

Nice to Have

• Experience with sensor data (radar, LiDAR, satellite, RF, etc.)
• Knowledge of tracking or filtering techniques (e.g. Kalman Filters, Bayesian methods)
• Background in remote sensing or sensor fusion
• Experience deploying models into production systems

We’re partnered with a growing technology business developing advanced data-driven systems that operate in complex, real-world environments.