Data Scientist

Our defence client, requires a new Data Scientist for their central team. Fully remote working available

Key Responsibilities

• Design, develop, and deploy advanced data science models using Python to solve geospatial and spatial-temporal problems.

• Work with large, complex datasets including satellite imagery, sensor feeds, open-source data, and mapping services.

• Apply machine learning, spatial statistics, and AI to support use cases such as land use classification, network optimisation, and population dynamics.

• Conduct data wrangling, coordinate transformations, raster/vector processing, and feature engineering.

• Create reproducible workflows and automate pipelines for data ingestion, analysis, and reporting.

• Produce clear and interactive visualisations using dashboards, maps, and data products.

• Collaborate with stakeholders, analysts, and policy teams to scope problems and communicate insights effectively.

• Ensure ethical use of data and support data governance and model transparency principles.

Essential Skills and Experience

• Expert-level Python programming, including libraries such as Pandas, NumPy, Scikit-learn, GeoPandas, Rasterio, Shapely, and PyProj.

• Proficiency in geospatial tools such as QGIS or PostGIS, and experience with formats like GeoTIFF, Shapefile, and GeoJSON.

• Proven track record of developing and deploying data science models

• Experience with SQL and spatial databases (PostgreSQL/PostGIS).

• Familiarity with cloud platforms (eg, AWS S3, Lambda, SageMaker, or GCP/Azure equivalents).

• Excellent problem-solving, collaboration, and communication skills.

Desirable Experience

• Experience with satellite imagery or remote sensing data (eg, Sentinel, Landsat, Copernicus)

• Strong experience working with geospatial data (raster and vector formats), spatial joins, and coordinate reference systems

• Knowledge of tools such as GDAL, xarray, Dask, or Google Earth Engine.

• Experience creating interactive dashboards with Plotly, Dash, or Streamlit.

• Exposure to Real Time data processing, mobility data, or urban analytics.

• Background in geography, environmental science, civil engineering, or a similar field.