Geospatial data scientist

Salary: £70,000 - 80,000 per year Requirements: Strong background in geospatial or spatial data science Experience working with Python and geospatial libraries such as GeoPandas, GDAL, and Rasterio Solid understanding of machine learning and statistical modelling Experience working with complex or large-scale datasets Ability to work effectively in a cross-functional engineering environment Experience with sensor data such as radar, LiDAR, satellite, or RF is desirable Knowledge of tracking or filtering techniques such as Kalman Filters or Bayesian methods is desirable Background in remote sensing or sensor fusion is desirable Experience deploying models into production systems is desirable Responsibilities: We develop algorithms for spatial data correlation and fusion We analyse and integrate multi-sensor datasets, including radar, LiDAR, RF, and imagery We build machine learning models for classification, regression, and tracking We apply statistical techniques to quantify uncertainty and improve predictions We perform feature engineering and dimensionality reduction on spatial data We build tools to visualise and validate model outputs We work closely with engineers to deploy models into production systems Technologies: Machine Learning Python Sensor Fusion More: We are partnering with a growing technology business developing advanced data-driven systems that operate in complex, real-world environments. Our work sits at the intersection of geospatial analytics, machine learning, and multi-source data, tackling challenging problems around data correlation, tracking, and real-time decision-making. We are building a newly formed data science team focused on spatial analytics and multi-sensor data fusion, and this role is remote with UK-based working, offering a salary of up to £80,000 plus bonus. We are looking for someone who wants to shape how spatial data is used across our platform and contribute to impactful, real-world solutions. last updated 25 week of 2026