Join us for an evening of Tech talk, trading games and networking!
Tech Talk: Data Mining usage patterns for building the right thing, building the thing right and supporting the thing better!
This talk will cover how Data Analysis and Machine Learning from usage patterns across large data sets is being used to predict bug reports, improve automated testing, and make tough decisions on what features to add to our software. We realised that data gathered for regulatory audit purposes, on millions of daily trades at Bloomberg, is an invaluable resource for analysis of our system’s behaviour.
In this talk, we’ll share the various opportunities this data has uncovered, the techniques we used for statistical
analysis-based machine learning, and the data visualization behind it. The work we’re planning and discoveries we’ve made promise to answer some very hard questions around prioritizing features to implement, reducing support costs, improving the automated test coverage and beyond. This also spawned an automated testing framework that allows the system to self-test by replicating the millions of daily trades in a secure test environment to achieve quality assurance. This has opened up horizons to build autonomic systems in the future — systems that can both self-test and self-repair
The talk will be followed by the Bloomberg Trading Game! This is a fun simulation where participants will be invited to understand the financial markets and trading activities through an active, sometimes frantic team trading game. Mentors will show you how to play the role of traders, sales and market makers and understand how these different players add value to the trading ecosystem.
This is a great opportunity to learn how Bloomberg’s technologies help bring transparency and efficiency to the exciting and sometimes volatile financial markets.
Food and drink will be provided.