Oxford Economics
Spatial Data Scientist
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Department: Cities & Regions
Location: London, UK
Description
Oxford Economics is a global leader in city and regional economic analysis, combining advanced data science with deep economic expertise. Our Cities Team forecasts thousands of locations worldwide, integrating economic models with geospatial analytics to drive decision-making across real estate, financial services, government, and beyond. We are seeking a Spatial Data Scientist to contribute to our growing portfolio of location intelligence research and geospatial modelling work.
The role sits at the intersection of economics, spatial data science, and geospatial analysis. You will work alongside economists, data scientists, and software engineers to develop innovative datasets, forecasting methodologies, and location intelligence products that help clients understand how cities and regions develop. The role combines applied quantitative analysis, spatial modelling, data engineering, and product development — with exposure to a global client base across both subscription services and bespoke consultancy projects.
Key Responsibilities
- Design and build spatial economic models to analyse urban economic performance, spatial disparities, and geographic drivers of economic activity
- Contribute to the development of city, regional, and sub-national forecasting methodologies.
- Build and maintain Python-based data pipelines to process, integrate, and analyse large geospatial datasets.
- Work with a wide range of data sources, such as Census data, satellite-derived indicators, global buildings and transport datasets, administrative boundaries, and Oxford Economics forecasts
- Apply machine learning techniques for classification and regression tasks on spatial and economic data
- Conduct advanced spatial analyses, like geographically weighted regression, spatial autocorrelation analysis, and spatial autoregressive modelling
- Support the development of scalable location intelligence products, digital tools, and analytical workflows. Contribute to location intelligence tools and products, including map-based visualisations and interactive dashboards
- Prepare clear written outputs to communicate technical findings to non-specialist audiences
- Collaborate across the Cities Team and with other Oxford Economics teams on cross-functional projects
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Skills, Knowledge & Expertise
We are open to candidates at an early-to-mid career stage, including those with postgraduate research experience, who can demonstrate strong quantitative and programming skills alongside an interest in cities, regions, and economic analysis. We are looking for someone technically capable, curious, and keen to develop in a research-led environment.
- Degree in economics, geography, data science, statistics, or a closely related discipline (postgraduate preferred)
- Strong proficiency in Python for spatial data analysis. Experience working with packages like geopandas, shapely, polars, folium, duckdb, OSMnx and developing modern version-controlled workflows using Git or similar systems.
- Experience working with vector/raster data, spatial indexing, and coordinate reference systems Experience building reproducible analytical workflows and data pipelines.
- Knowledge of socioeconomic concepts relevant to sub-national analysis is highly desirable
- Experience working with APIs, cloud-hosted datasets, or large tabular/geospatial data at scale
- Competent with data visualisation tools
- Strong written communication: ability to distil technical results into clear, accessible outputs
- Ability to manage own workload across multiple concurrent projects
- Genuine interest in cities, regions, urban economics, location intelligence, or related fields.
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Desirable extras: Knowledge of economics, economic geography, urban economics, regional economics, or economic forecasting. Experience with geospatial APIs (Mapbox, Google Maps Platform, OpenStreetMap, R5), exposure to EViews or similar econometric software, or experience building interactive web tools.
How To Apply
Please submit a covering letter and CV. Your covering letter should explain how you meet the requirements above and include a brief example of a spatial analysis or data science project you have completed — academic, professional, or personal. We welcome applications from candidates who may not tick every box but can demonstrate strong technical ability and genuine enthusiasm for the intersection of economics and geospatial data.
Job Benefits
Here are some of the benefits we offer in the UK to ensure you feel valued, supported, and thrive at work:
- Private Healthcare
- Employee Assistance Program
- Enhanced Maternity and Paternity Leave
- Workplace Nursery Scheme
- Cycle to Work Scheme
- Hybrid/Flexible Working
- Team Gatherings and Connection Boost!
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