Charles Cai has more than two decades of experience and track record of global transformational programme deliveries – from vision, evangelism to end-to-end execution- in global investment banking, and energy trading companies where he excelled 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 then Head of Data Science at a leading Oil and Gas trading company, and previously at Investment Banks, he has earned a reputation of a leading expert, true innovator, disruptor and intrapreneur in Front Office commodity trading and risk management; in recent years, he has been an evangelist and practitioner in Big Data and Data Science practices. Charles brings in a huge experience and expertise in designing and implementing Data Science platforms with software-defined data center open source projects and data scientist tooling. He’s a frequent speaker at Google Campus, Big Data Innovation Summit, Cloud World Forum, Data Science London, QCon London and MoD CIO Symposium etc, promoting knowledge and best practice sharing with audience ranging from developers, data scientists, to senior executives from both IT and business background.
Over the last 2 years, he has been leading projects like distributed machine learning of global energy flow prediction, scalable and secured on-Prem and Cloud Big Data architecture, Big Data / Data-Science-as-a-Service. He also advises CXO level executives in Retail, Commercial & Investment Banking, Asset Management, Publishing, Media, eCommerce, Insurance, and Telecommunications on disruptive technologies and business models, and hands-on machine learning practices. He was a co-founder to have built a global private bank which went public in HKSE in 2013. In his spare time, he attends and has won a few hackathons awards. He also helps organize meetups and hackathons for Data Science London, a non-profit-organization with 5000 data scientists registered in UK and Europe, with recent ones like Xbox Gaming Hack at Microsoft campus, Urban Air Quality Hackathon at Future Cities Catapult and Urban City Innovation Centre. He aims to provide this crowdsourcing model with a state-of-the-art data science platform capable of serving 800-1000 data scientists globally in 8-10 cities to tackle life science challenges later this year, partnered with Alzheimer Society.
He has advanced knowledge and experience in Scala, Python, C# / F#, C++, Java, R, Haskell programming languages. He’s a certified TOGAF9 architect, certified EMC Associate data scientist, and certified CNE4 Novell network engineer. Charles holds a BSc Hons in Electronic Engineering, EIS (Electronics and Information Systems), from Fudan University (Shanghai, China).