Role overview
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.
What you'll work on
- Applying quantitative techniques to large complex datasets using R and/or Python
- Design, build and deploy econometric and machine learning models for clients across the consultancy business
- Communicating with clients effectively, responding promptly and positively to their enquiries, with progression to handling and developing client relationships
- Working with colleagues to develop research proposals and project reports
- Being able to plan and structure your own project work, ensuring sufficient time for quality assurance from senior colleagues
- Taking the initiative in suggesting ways to strengthen the quality of our analysis through creative solutions
- Taking the lead on technical aspects of project work, with progression to managing projects
What we're looking for
Required**
- 2-5 years’ professional experience in data scientist or applied economics
- Familiarity working with at least one cloud platform provider (e.g AWS, GCP, Azure)
- Experience working in a collaborative environment using version control software (e.g Git)
- Experience building and deploying machine learning models (supervised, unsupervised, and/or deep-learning models)
- Familiarity with modern generative AI concepts (e.g embeddings, RAG pipelines, fine-tuning)
- Strong programming skills in Python; desirable to have at least one other such as R, SQL, JavaScript, etc
- Experience working with a variety of structured and unstructured data
- Excellent written and verbal communication, including the ability to explain economic concepts and quantitative results to non-specialists
- Experience building UI dashboards to visualise and engage with complicated data (e.g. Streamlit, PowerBI, etc.)
- An understanding of using containerised workflows (e.g Docker)
Desired
- A postgraduate degree in economics or a closely related quantitative discipline
- Experience conducting economic analyses using large complex datasets, for example company procurement databases, survey microdata, Bloomberg, etc.
- Experience working with a deep-learning framework such as PyTorch or TensorFlow