Job Summary:
If you are passionate, curious, and ready to make an impact, we are looking for you.
Quantitative Research (QR) is an expert quantitative modelling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modelling and portfolio management. As a global team, QR partners with traders, marketers and risk managers across all products and regions, contributes to sales and client interaction, product innovation, valuation and risk management, inventory and portfolio optimization, electronic trading and market making, and appropriate financial risk controls.
We are looking for a talented Quant to join the Quantitative Research Securities Services global team. The role is based in London. The Securities Services business holds $27tn of Assets under Custody (AUC) and more than $200bn of cash, providing opportunities for Quantitative Research to add value through innovative use of data analytics and machine learning.
You will be a part of a team that is helping to transform business practices though data science and other quantitative methods where JP Morgan is already a dominant player, handling trillions of dollars of client assets. Your first responsibility will be to contribute to various machine learning projects on a cloud platform.
In addition, we are providing on job training, intensive internal classroom training, and online courses, all given by our experienced quants. Through the diversity of the businesses, it supports and the variety of functions that it is responsible for, Quantitative Research group provides unique growth opportunities for you to develop your abilities and your career.
Job responsibilities:
- Help to lead Quantitative Research’s transition to the cloud.
- Leverage cloud infrastructure to perform large-scale analysis on gigantic financial data from $1 trillion+ daily transactions and $200 billion+ cash
- Lead machine learning projects from research stage into production deployment with a state-of-the-art Python development environment
- Make real-world, commercial recommendations through effective presentations to various stakeholders
- Leverage data visualization to communicate quantitative insights to help business decision making
Required qualifications, capabilities, and skills:
- You bring computer programming experience in Python: pandas, numpy, scikit-learn, tensorFlow, SDLC, clean code fundation
- You demonstrate experience applying Machine learning knowledge in supervised learning models such as Random Forests, boosted trees, and neural networks
- You demonstrate proficiency in applying cloud computing experience: e.g. AWS (S3, EC2, etc.), Kubernetes, Google Cloud, Microsoft Azure
- You have excellent communication skills, both verbal and written with ability to present findings to a non-technical audience
Preferred qualifications, capabilities, and skills:
- Advanced degree (PhD, MSc or equivalent) in a quantitative field (Computer Science, Mathematics, Physics, Statistics, Quantitative Finance, Economics )
- Experience in using SQL
- Participation in Kaggle competitions or contributions to GitHub
Beyond that, we’re interested in the things that make you unique: personal qualities, outside interests and achievements beyond academia and profession that demonstrate the kind of person you are and the differences you could bring to the team.