Geospatial Data Scientist

About the Role

Oxford Economics is looking for a Geospatial Data Scientist to join their cities team. This role involves enhancing the use of data science and spatial analytics within city regional economic monitoring and forecasting services, and related location analytics projects. The cities team produces datasets and forecasts for thousands of regions globally, often using geospatial datasets and machine learning to supplement data, particularly in areas like estimating GDP, analysing urban dynamics, and quantifying physical risks associated with climate change. A recent example includes using satellite imaging, specifically night-time lights datasets, to produce hyper-localised estimates of GDP for assessing economic vulnerability to climate-related physical risk events. The team continuously improves and enhances data modelling and processing systems with new models, datasets, and software. The successful candidate will work on multiple research projects, contributing to methodologies, data analysis, deliverable drafting, and client presentations. With experience, they will progress to designing analytical frameworks, leading client interactions, and project management. Collaboration with other Oxford Economics teams and working with diverse global clients are key aspects of this role, requiring strong written and verbal communication skills.

Key Responsibilities

• Developing innovative geospatial datasets to enhance estimates of regional economic activity and trends.
• Undertaking robust and rigorous analysis in the delivery of consultancy projects, applying quantitative analytical techniques to large datasets using various tools.
• Building solutions to support clients in making better-informed decisions using different forecasting methods, statistical models, and GIS solutions.
• Taking the lead on aspects of project work, managing them from inception to completion, and addressing challenges, including managing whole projects with project director support.
• Working with senior colleagues to develop research proposals, innovative methodologies, and proposals to meet client requirements.
• Taking the initiative in suggesting ways to strengthen the quality of analysis, including exploring new areas of application, with progression to proactively developing new business opportunities.
• Communicating effectively with clients and potential clients, responding promptly and positively to enquiries, with progression to leading on existing and potential client relationships.
• Planning and structuring your own workload, balancing priorities across projects and other responsibilities with line manager support, with potential for progression to line management responsibilities.
• Supporting the continued development of the team, sharing knowledge and expertise, mentoring junior colleagues, and bringing new ideas and techniques to the team.

Candidate Requirements

The successful candidate should have a genuine interest in data analytics and economics, with 3 to 5 years of professional experience in a comparable position. Key skills and qualifications include:

• Strong academic education in economics, geography, computer science, or a related discipline.
• Excellent analytical and quantitative skills.
• Experience in using database programming languages and software such as R, Python, Stata, QGIS, or EViews.
• Experience with geospatial-specific statistical modelling, such as geographically weighted regression, spatial autoregressive modelling, as well as traditional econometric models.
• Experience with leveraging machine learning techniques for both classification and regression outputs.
• Experience in analysing and modelling large geospatial datasets using GIS and/or statistical modelling software.
• Strong written and verbal communication, including the ability to explain technical concepts and quantitative results to non-specialists.
• Experience with climate variables and/or climate modelling is desirable but not required.