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Spatial Data Scientist

Oxford Economics · London, GB

Job 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. Department Cities & Regions Employment Type Full Time Location London, UK Workplace type Hybrid 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 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.

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!

About Oxford Economics

Oxford Economics was founded in 1981 as a commercial venture with Oxford University’s business college to provide economic forecasting and modelling to UK companies and financial institutions expanding abroad. Since then, we have become one of the world’s foremost independent global advisory firms, providing reports, forecasts and analytical tools on more than 200 countries, 250 industrial sectors, and 7,000 cities and regions. Our best-of-class global economic and industry models and analytical tools give us an unparalleled ability to forecast external market trends and assess their economic, social and business impact.

Headquartered in Oxford, England, with regional centres in London, New York, and Singapore, Oxford Economics has offices across the globe in more than 15 cities. We employ more than 400 professional economists, industry experts and business editors—one of the largest teams of macroeconomists and thought leadership specialists. Our global team is highly skilled in a full range of research techniques and thought leadership capabilities, from econometric modelling, scenario framing, and economic impact analysis to market surveys, case studies, expert panels, and web analytics.

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