Jeremy is a Lead Data Scientist at the Data Science Campus, having joined the ONS permanently in July 2018.
Jeremy oversees our economic insights workstream, which uses novel data sources and data science techniques to create new, granular and timely economic statistics and analysis.
He has worked as part of the ONS’s efforts to develop more real-time indicators of the economy and society, harnessing new data sources, for example VAT and ship tracking data.
Prior to joining the ONS, he worked as an economist at the Bank of England, providing analysis for the Monetary Policy Committee. He worked on a range of topics including GDP forecasting, trade, household debt and inflation expectations. During his time at the Bank of England he built experience in survey design, data visualisation and data science techniques.
He is interested in building and analysing large and innovative datasets to generate new insights, which support policy makers and the public in their decisions.
He holds a BSc and MSc in Economics from Warwick University and University College London respectively. He has also been involved in projects with the Economics Statistics Centre of Excellence.
Outside of work he is involved in a local church and enjoys playing 5-a-side football and tennis.
This report is part of a programme of work that the ONS has been doing with the Alan Turing Institute to explore the usefulness of various economic nowcasting methods, particularly the signature method.
Read more on Technical report: nowcasting UK household income using the new “signature” method
Nowcasting refers to generating estimates of the current (“now”) state of the economy. We investigate how signature methods can be useful in the context of economic nowcasting
Read more on Helping decision makers understand the economy quickly through new methods
A report on the quality and methodology of data used to produce extent and change of surface water statistics for reporting on Sustainable Development Goals indicator 6.6.1 for the UK.
Read more on Quality and methodology: Extent and change of surface water statistics
In this blog, we describe how we have assessed the quality of the novel Global Surface Water Explorer (GSWE) dataset to better understand its value and fitness-for-purpose, producing data to report the UK’s position on indicator 6.6.1.
Read more on Using satellite imagery to report changes to water bodies for SDG 6.6.1
Extracting social-economic signals from internet traffic data.
Read more on What can internet use tell us about our society and the economy?