03 November
1.10pm, LT308 Huxley
| Title: | Data Science for Physical Energy Trading Insights |
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| Abstract: | BP p.l.c Trading Division, a.k.a. IST, Integrated Supply and Trading, is increasingly leveraging Data Science and machine learning technologies to uncover insights from public and private data sets, for example, weather, global financial markets, vessel movement (there are 100,000 of them), geopolitical events, to draft global energy supply and demand flow so we can help operators and traders to make informed decision on risk management and new trading opportunity discovery. In this talk, I’ll show you the size of the energy market and BP’s role in it, visualisation of the interesting datasets we are dealing with, and our current thoughts around emerging technologies and where you might play an important role! |
| Speaker Details: | Charles Cai @caidong #DataScience, #Intrapreneur #Innovator #Disruptor in #ETRM #FO #MO #BO w/ #BigData #ML #IoT #Mobile #Cloud #UI #UX #FP #startup Charles Cai has more than two decades of experience and track records of global transformational programme deliveries - from vision, evangelism to end-to-end execution in global investment banks, and energy trading companies, where he excels at designing and building innovative, large scale, Big Data systems in high volume low latency trading, global Energy Trading & Risk Management, and advanced temporal and geospatial predictive analytics, as Chief Front Office Technical Architect and Head of Data Science. He’s also a frequent speaker at Google Campus, Big Data Innovation Summit, Cloud World Forum, Data Science London, QCon London and MoD CIO Symposium etc, to promote knowledge and best practice sharing, with audience ranging from developers, data scientists, to CXO level senior executives from both IT and business background. He has in-depth knowledge and experience in Scala, Python, C# / F#, C++, Java, R, Haskell programming languages, and TOGAF9, EMC-DS, AWS CNE4 etc. certifications. |
