Alfredo Mungo, consultant with Quanteam UK since February 2017, is a Software developer working with the Business Data Intelligence (BDI) team of a French client. Passionate about Data Science and Machine Learning, Alfredo had a chance to attend the Open Data Science Conference 2018 in London.
Quanteam UK is committed to ensuring that their consultants can develop their skills and professionalism to build their career, but also to deliver the best services to clients. Within this perspective, Alfredo had the opportunity to spend 4 days at the Open Data Science Conference 2018 in September, to investigate and develop his understanding of the impact and use of Data Science within the Financial Markets industry. He now shares his experience with us, and reflects upon the contribution of Data Science to the industry generally, and also in his team.
“Most of the talks were focussed on optimising the techniques leveraged in the building, testing, maintenance and deployment of machine learning pipelines both for research purposes and production. The workshops guided attendees through various topics showing how Machine Learning and more broadly Data Science apply to the financial sector, such as:
· reinforcement learning
· various leakage situations due to bad practices, that lead to poorly performing final models and the ways to avoid them
· algorithmic stock trading by using machine learning pipelines
· online data providers leveraging deep learning to understand patterns in the data and using neural networks to extract information from financial documents. “
“Although the application of some techniques to the banking industry may not seem immediate at first glance, the power of these lays in their abstraction"
“In terms of technology, Jupyter notebook, Pandas and Scikit-learn were frequently used across the different sessions.” These technologies – more and more used by a lot of teams dealing with a huge amount of Data – are Python applications and libraries mostly used for Data analysis and mining as well as Machine Learning.
“Being a data science event, not all the talks and workshops were about Machine Learning so I took the chance also to attend a few sessions about statistics and data visualisation, where I could see how expert researchers handle time series analysis and produce outstanding reports about the finding of their studies, tailoring them to their audience.
Although the application of some techniques to the banking industry may not seem immediate at first glance, the power of these lays in their abstraction. All these algorithms are generic and can easily be abstracted from the specific use case of the workshop to many other situations in the most diverse contexts.
With BDI constantly working with data reporting and manipulation and RISK (Risk department of the Bank – Editor’s Note) moving more and more towards data science, all statistics, machine learning and data visualisation sessions proved useful in deepening my understanding of some well-known algorithms, giving me insights for new areas of data science to focus my studies on and provide a better experience to RiskLab customers when helping them build data-oriented applications that require deep knowledge of data manipulation and visualisation.”
More generally, financial institutions tend to resort more and more to Data Science techniques, in several types of environments for which the application of Machine Learning is crucial. Following this trend, we observe that lots of Investment Banks in the City are currently building and developing Innovation Labs, focusing on bringing Machine Learning expertise into the Banking sector. For instance, Algorithmic Trading as well as Fraud Detection are both major business areas where the use of these technics and technologies are fully explored, and to which we contribute.
Today, Quanteam UK is partnering with several Data Science projects for major clients. That is why the development of our Consultants’ skills in this field is one of our key priorities.
If you too, you want to join Quanteam UK’s adventure, and contribute to these highly skilled Data Science projects, apply here!
We thank Alfredo for his contribution! If you want to know more about his experiences and background, have a look at his LinkedIn profile here!