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Geospatial Data Scientist

Technify Talent
Department:Data Analysis
Type:REMOTE
Region:UK
Location:England, United Kingdom
Experience:Mid-Senior level
Salary:£80,000 - £80,000
Skills:
GEOSPATIAL DATA SCIENCEPYTHONGEOPANDASGDALRASTERIOMACHINE LEARNINGSTATISTICAL MODELLINGDATA ANALYSISSENSOR DATAKALMAN FILTERSBAYESIAN METHODSREMOTE SENSINGSENSOR FUSIONMODEL DEPLOYMENT
👁️ Views: 14🚀️ Applied: 3
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Job Description

Posted on: March 25, 2026

Geospatial Data ScientistRemote (UK-based)Up to £80,000 + BonusThe Opportunity

We’re 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 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 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

What They’re Looking For

  • 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

If you’d like to learn more about the role, team, or technology, feel free to apply or reach out for a confidential chat.

Originally posted on LinkedIn

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👁️ Views: 14🚀️ Applied: 3
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