Very few of us work at a start-up. Many of us work for larger, older institutions. Such organisations have well developed processes that can be difficult to change. Firms such as these have enterprise wide agreements with software providers, must go out to tender for new software and have complicated legacy systems. The Bank of England is such an institution.
But that doesn’t mean such institutions are places bereft of Data Science (DS)… far from it! Having worked at the Bank for over 13 years I know this is the best time there has ever been to be interested in DS and work there. This talk will exhibit some of the many ways the Bank using DS to deliver insight and how it advances DS internally. Highlights include:
Delivering DS projects with people unfamiliar with DS
Talk about our internal communities of practice (I am co-chair of the R one)
Bringing colleagues together via a tight-knit community.
Finally, we will look at practical examples of utilising legacy systems using R and demonstrating how R can do things better than closed source tools. There will be some others bits too (can’t give everything away in the abstract!).
Daniel Durling has worked at the bank of England for 13 years in a variety of data roles, most recently in Advanced Analytics, the PRA Data & Innovation Team and now in the Data Analytics Project Pool. He lives in Manchester with his partner, and in his spare time he enjoys cycling, watching professional wrestling (the only true sport) and taking a data-driven approach to making the perfect cup of coffee.