Applications for this job are now closed
BNP Paribas Global Markets provides cross-asset investment, hedging, financing, research and market intelligence to corporate and institutional clients, as well as private and retail banking networks.
Global Markets' sustainable, long term business model seamlessly connects clients to capital markets throughout 38 markets in EMEA, Asia Pacific and the Americas, with innovative solutions and digital platforms.
Through Global Markets, clients can access a full universe of opportunities in equity derivatives, foreign exchange and local markets, commodity derivatives, rates, primary and credit markets and prime solutions and financing.
The Role
The Graduate Program is designed to provide you with first-class training and immediate responsibility. You will participate in a 3 week induction before moving into a full-time role in one of our quant teams.
As a graduate you will have access to a number of workshops, in-house training and networking events. You will also be assigned a mentor to help you with your career development.
The role of our Data and A.I Lab is to use the latest techniques of Machine Learning, Artificial Intelligence and Natural Language Processing to help Global Markets do a better job.
For this, we need to leverage the huge amount of both internal and external data we are accumulating daily, whether it is structured (Market and Trade data) or unstructured (Chats, Voice conversations, Social Media and alternative data).
What you will do
Your role will include:
- Using the latest techniques of Machine and Deep Learning to build models for our trading and sales activity leveraging internal and external data to improve the service we give to Clients while managing tightly the risk associated to those products
- Build our next generation of Natural Language Understanding interface (Speech to Text and Chat to Systems) across all business lines
- Participate in the design and development of our core research projects such as unsupervised classification of the various market participants behaviour, sentiment analysis in chats or new and improvement of the market making in low or high frequency
- Be able to innovate freely, Introducing new techniques or technologies if needed
Technical Skills Required
- Strong education in Statistics, Maths or Computer Science (Master or PhD level): we are not just looking for people who know how to use machine learning techniques, but for people who understand how it works inside the black-box.
- Strong knowledge of Machine Learning techniques (classification, regression, natural language processing via standard statistical models or neural network)
- Good programming skills, preferably Python
- Good knowledge of Databases (SQL, Oracle, MongoDB…) and with dealing with Big Data environment (Hadoop, Spark)
- Relevant internships in industry applying Machine Learning techniques and successful participation to Kaggle challenges are a plus
- Delivery-driven mindset
- Strong interpersonal skills and proactive approach to problem solving
- Ability to work under pressure and multi-task
- Strong organisational skills
- Team Player
Conduct
- Be a role model, supporting and fostering a culture of good conduct
- Demonstrate proactivity, transparency, and accountability for identifying and managing conduct risks
- Consider the implications of your actions on colleagues
