Leveraging alternative data, machine learning, and advanced empirical methods such as causal inference, Barclays’ Data Science and Investment Sciences teams work to provide institutional clients with next-level insights and actionable ideas.
The Data Science team focuses on developing data science methods and building the infrastructure to work with data at a large scale, while the Investment Sciences team integrates data science into the investment research process across all asset classes.
Clients benefit from data science-informed research written in collaboration with a wide range of research analysts, especially equity and credit fundamental analysts, as well as proprietary algorithms and products that are derived from alternative data.
A key focus is on transparency and reproducibility, so clients will often find code attached to our research reports. We’re happy to discuss details of our analysis, data sources and infrastructure to help our clients produce their own differentiated insights.
Spend Trends is a set of signals designed to provide an in-depth view into consumer spending in the UK.
Data Science Notes blog
Looking to build or refine your own data science capabilities? Read the blog by our Data & Investment Sciences teams, which dives into frequently asked questions about data science and how it is reshaping investing.