At a Glance
- Tasks: Design spatial economic models and build data pipelines for urban analysis.
- Company: Join Oxford Economics, a leader in city and regional economic analysis.
- Benefits: Enjoy private healthcare, flexible working, and enhanced parental leave.
- Other info: Collaborative environment with opportunities for career growth and learning.
- Why this job: Make an impact on urban development with innovative location intelligence research.
- Qualifications: Degree in economics, geography, or data science; strong Python skills required.
The predicted salary is between 50000 - 65000 £ per year.
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.
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.
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!
Spatial Data Scientist employer: Oxford Economics
Oxford Economics is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets economic analysis. With a strong focus on employee growth, we provide opportunities for professional development through collaboration with experts in economics and data science, alongside a comprehensive benefits package that includes private healthcare and flexible working arrangements. Join us to contribute to impactful projects that shape the future of cities and regions while enjoying a supportive and inclusive workplace culture.
StudySmarter Expert Advice🤫
We think this is how you could land Spatial Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your spatial data projects, analyses, and any cool visualisations you've made. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and practising common questions related to spatial data science. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team at Oxford Economics.
We think you need these skills to ace Spatial Data Scientist
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Spatial Data Scientist role. Highlight your experience with Python, spatial data analysis, and any relevant projects that showcase your skills in urban economics and geospatial modelling.
Showcase Your Technical Skills:We want to see your technical prowess! Include specific examples of how you've used Python and relevant libraries like geopandas or shapely in your previous work. This will help us understand your hands-on experience with spatial data.
Communicate Clearly:Remember, you’ll need to explain complex ideas to non-specialists. Use clear, straightforward language in your written application to demonstrate your ability to distil technical findings into accessible outputs.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Oxford Economics
✨Know Your Spatial Data
Make sure you brush up on your knowledge of spatial data analysis and the tools mentioned in the job description, like Python and its relevant packages. Be ready to discuss how you've used these tools in past projects or research.
✨Showcase Your Analytical Skills
Prepare to demonstrate your quantitative and analytical skills. Think of specific examples where you've applied machine learning techniques or conducted advanced spatial analyses. This will show that you can handle the technical demands of the role.
✨Communicate Clearly
Since you'll need to distil complex findings for non-specialist audiences, practice explaining your past work in simple terms. This will help you convey your ideas effectively during the interview and highlight your strong written communication skills.
✨Express Your Curiosity
Let your passion for cities, regions, and economic analysis shine through. Be prepared to discuss why you're interested in this field and how you stay updated on trends and developments. This enthusiasm can set you apart from other candidates.
