8 of 8 Remote/Hybrid Spatial Analysis Jobs in England

repeatable workflows, provide technical assurance and peer review, mentor colleagues, support bids and client engagement, and drive innovation in marine spatial analysis, data services, dashboards, web applications and digital products. The role also includes line management responsibility. You are a highly organised, proactive, collaborative and self‐motivated … geospatial solutions in a consultancy or commercial environment. Strong capability in Python, ArcPy, ArcGIS API for Python and ModelBuilder, developing automated, repeatable workflows for analysis, data management, QA/QC and reporting. Proven experience designing and supporting web GIS applications and services, including Experience Apps, Dashboards, StoryMaps, Survey123 ...

wider business stakeholders; design and maintain robust spatial datasets; develop and manage web based GIS applications; and apply spatial analysis to support due diligence across UK and international investment portfolios. Through the establishment of standardised geospatial processes, auditable data workflows and high-quality visualisations … strategy to become a data-driven, technology-led and AI-infused enterprise. KEY RESPONSIBILITIES Analytics & Insight Generation: Lead spatial and environmental analysis across ESG topics, integrating survey, CAD, consultant and public datasets to identify constraints, risks and opportunities, and translating complex geospatial data into clear, actionable insight ...

proven track record of successfully delivered work across the ML lifecycle and a strong foundation in statistical modelling, natural language processing, time-series analysis, spatial analysis, and mathematical modelling methodologies. Keen to demonstrate the potential that Agentic & Gen AI has to offer to unlock business value. ...

Geographic Information Systems (GIS) and open-source geospatial tools, helping clients unlock the value of location data through innovative mapping and spatial analysis solutions. Role Responsibilities This is a varied role that calls for adaptability, ambition, and a proactive approach to working in a fast-paced, agile ...

Proven experience working with geospatial data, including handling spatial formats (e.g., vector, raster, GeoJSON, shapefiles), coordinate reference systems, and spatial analysis workflows Strong ability to interpret and apply geographical context in data processing pipelines, with demonstrated capability to aggregate, upscale, or translate local/regional ...

transport, dispersion modelling or environmental data analysis. Excellent analytical skills with the ability to interpret complex real‐world datasets. Strong Python skills for scientific analysis (NumPy, Pandas, SciPy or similar). Experience communicating technical findings to both technical and non‐technical audiences. Ability to work collaboratively across software, engineering … biogas or similar industrial environments. Knowledge of emissions reporting frameworks such as OGMP 2.0 or measurement‐informed inventories. Experience with GIS, spatial analysis, atmospheric modelling or computational fluid dynamics (CFD). Exposure to lidar, spectroscopy, remote sensing or optical measurement technologies. Understanding of scientific software development, version ...

Design, implement, and maintain robust C++ software for geospatial and sonar data processing. Develop high-performance workflows for spatial analysis, mapping, and data fusion. Optimise code for speed, scalability, and memory efficiency across Windows and Linux platforms. Collaborate with data scientists and engineers to integrate C++ modules ...

commercial questions into analytical problems and ensuring our models deliver meaningful business value. Rigorously validate models through out-of-time testing, leakage checks, sensitivity analysis and clear measures of uncertainty, ensuring every input genuinely reflects the information available at the point a decision is made. Develop approaches for locations … evidence to trust a result. Work with Engineering and Data colleagues to turn model outputs into reusable, scalable data assets rather than one-off analysis or tables . Partner with MLOps colleagues to deploy, monitor and retrain models, with clear ownership, versioning in MLflow and documented handover points. Turn ...