Geospatial Data Scientist
Remote (must be UK-based)
Up to £80,000 + Bonus
The Opportunity
Technify Talent have partnered with a growing technology business developing advanced data-driven systems that operate in complex, real-world environments.
Their 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.
They're now looking for a Geospatial focused Data Scientist to play a key role in solving these problems and shaping how spatial data is used across their platform.
The Role
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 applied statistics, machine learning, geospatial data, and mathematical modelling, with a strong emphasis on solving real-world problems, particularly around quantifying and managing uncertainty across multiple data sources.
What You'll Be Doing
* Developing algorithms for spatial data correlation and fusion
* Analysing and integrating multi-sensor datasets
* Applying statistical techniques (Bayesian methods, Kalman/particle filtering, and other uncertainty quantification approaches) to improve predictions and manage uncertainty across data sources
* Building machine learning models for classification, regression, and tracking
* 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
What We're Looking For
* Strong background in applied statistics, spatial data science, or a related quantitative field
* Experience working with Python; geospatial libraries (GeoPandas, GDAL, Rasterio etc.) are a plus but not essential
* Solid understanding of statistical modelling and uncertainty quantification, e.g. Bayesian methods, Kalman or particle filtering
* Experience working with complex or large-scale datasets
* Ability to work in a cross-functional engineering environment
* Experience deploying models into production systems
If you'd like to learn more about the role, team, or technology, feel free to apply or reach out for a confidential chat.
