Geospatial Data Scientist

Oxford Economics is seeking a Geospatial Data Scientist to join its Cities & Regions team in London. The role involves enhancing data science and spatial analytics for economic monitoring and forecasting, utilizing geospatial datasets and machine learning. Candidates should have 3-5 years of experience in economic geography or data science, with skills in processing satellite imagery and building algorithms in R, QGIS, or Python. Strong communication skills are essential for collaborating with diverse global clients.

Geospatial Data Scientist

Department: Cities & Regions

Employment Type: Full Time

Location: London, UK

Description

Oxford Economics, a leading economic forecasting and consulting firm, is looking for a Geospatial Data Scientist to join our cities team to help enhance the use of data science and spatial analytics within our city regional economic monitoring and forecasting services, and related location analytics projects. The cities team produce datasets and forecasts for thousands of regions globally, including markets where traditional datasets are scarce. We use geospatial datasets and machine learning to supplement our datasets across a number of fields; such as estimating GDP, analysing urban dynamics, and quantifying physical risks associated with climate change.

A recent example of our analysis in this field has been the introduction of geospatial datasets to our climate change scenarios product. To best assess the economic vulnerability of regions to the rising impacts of physical risk events such as flooding, wildfire, and drought, we needed to identify areas of economic activity at a hyper-local level. Our team used satellite imaging, particularly night-time lights datasets, to produce hyper-localised estimates of GDP. We then combined this understanding of economic activity with geospatial analysis of various climactic risks to create regional economic vulnerability scores to climate-related physical risk events.

The successful candidate will most likely be someone with experience in processing large-scale satellite imagery datasets (both vector and raster), and someone with experience in building machine learning algorithms for large-scale image processing and model building in R, QGIS, and/or Python.

Key Responsibilities

In this role, you will contribute to all aspects of the production, delivery and development of our existing city forecasting services. This includes:

1. Developing innovative geospatial datasets to enhance estimates of regional economic activity and trends;
2. Undertaking robust and rigorous analysis in the delivery of consultancy projects including applying quantitative analytical techniques to large datasets using a variety of tools;
3. Building solutions to support clients make better informed decisions using different forecasting methods, statistical models, and GIS solutions;
4. Taking the lead on aspects of project work, managing them from inception to completion addressing challenges along the way, including managing whole projects with the support of a project director;
5. Working with senior colleagues to develop research proposals, innovative methodologies, and developing proposals to meet client requirements;
6. Communicating with clients and potential clients effectively, responding promptly and positively to their enquiries;
7. Being able to plan and structure your own workload, balancing priorities across projects and other responsibilities;
8. Supporting the continued development of the team, sharing knowledge and expertise, and mentoring junior colleagues.

Candidate Requirements

The successful candidate should have a genuine interest in data analytics and economics and is likely to have 3 to 5 years of professional experience in a comparable position. Skills and qualifications relevant to this role include:

1. Strong academic education in economics, geography, computer science or related discipline;
2. Excellent analytical and quantitative skills;
3. Experience in using database programming languages using software such as R, Python, Stata, QGIS, or EViews;
4. Experience with geospatial-specific statistical modelling, such as geographically weighted regression, spatial autoregressive modelling, as well as traditional econometric models;
5. Experience with leveraging machine learning techniques for both classification and regression outputs;
6. Experience in analysing and modelling large geospatial datasets using GIS and/or statistical modelling software;
7. Strong written and verbal communication, including the ability to explain technical concepts and quantitative results to non-specialists.

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!

Equal Employment Opportunity (EEO)

Oxford Economics is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

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