Job Summary:
Quantitative Research (QR) is an expert quantitative modeling group in J.P. Morgan, as well as a leader in financial engineering, data analytics, statistical modeling 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 team in London. As part of the Corporate and Investment Bank, the Securities Services business holds $27tn of Assets under Custody (AUC) and more than $200bn of cash. Within Quantitative Research Securities Services, you will be part of the Cash, FX & Liquidity team that works closely with the global business in optimizing Net Interest Income, client pricing and managing intraday liquidity through the innovative use of data analytics, time series analysis and machine learning.
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:
- Perform large-scale analysis on gigantic financial data from $1 trillion+ daily transactions and $200 billion+ cash
- Develop quantitative models to predict client intraday liquidity usage and the evolution of our cash deposit balances throughout economic cycles
- Build sequential decision making tools to optimize the net interest income of the business under various liquidity, capital and balance sheet constraints
- Lead projects end-to-end, from brainstorming, prototyping, data processing, data analysis to model development
- 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:
- Advanced degree (PhD, MSc or equivalent) in Engineering, Mathematics, Physics, Computer Science, etc.
- You have a strong interests in applying statistics, optimization and machine learning to solve real-world problems
- You demonstrate experience in writing production quality code and familiarity with testing and source control
- You bring a data analytics experience using open-source Python packages (pandas/numpy/scikit-learn/tensorflow)
- You have a strong communication skills (both verbal and written) and the ability to present findings to a non-technical audience
- You demonstrate a strong intellectual curiosity, and an interest in understanding at a deeper level how a bank operates
- You demonstrate a strong desire to work with data and being comfortable in handling large datasets as well as building data pipelines
Preferred qualifications, capabilities, and skills:
- Participation in KDD/Kaggle competition or contribution to GitHub is a plus
- Familiarity with financial instruments, in particular fixed-income instruments is desirable
- Hands-on experience in solving sequential decision making problems is a plus