Joe is a Lead Data Scientist at JPMorgan and is currently working on applications of Natural Language Processing for media monitoring and content recommendation for various teams within the firm. Before that he worked on a big data framework timeseries anomaly detection. He has been at JPMorgan for over 5 years working in pure Python development roles, big data, machine learning and data science.
His background is an undergraduate in Avionics (Glasgow) and a PhD in Reinforcement Learning and Control Engineering (Cambridge) in which he wrote a lot of MATLAB code, and hand calculated a lot of gradients - he is now very thankful for Python and autograd!
How to automatically identify, and describe, interesting patterns in timeseries data, such as trends, change-points and periodic behaviour.