|Job Type:||Full Time|
Equities Cash Risk Quantitative Research
The Equities Cash Risk Quantitative Research team collaborates and partners with the Sales and Trading desks in the Equities Cash business with specific focus on developing quantitative analysis and research of trading activity, development of trading / unwinding strategies for the principal trading desk and central risk desk based on various market based alpha signals and client principal activity, automation, optimization, and hedging of trading positions managed by the desk.
Quantitative skills are at the core of J.P. Morgan’s capabilities, actively contributing to the competitiveness and innovative power of our firm. The team's mission is to develop cutting-edge next generation analytics and processes to transform, automate, and improve the trading operations of our Cash businesses. We work closely with traders to develop data-driven solutions such as algorithmic strategies (high to low frequency), trading signals, risk models, portfolio optimization, recommendation engines, flow categorization, and clustering – and to ultimately combine them into automated trading processes.
We are now seeking applicants for a Senior Associate position within the Equities Cash Risk Quantitative Research team in London. Seeking individuals passionate in areas such as electronic trading, machine learning, option pricing, optimization, computational statistics, and applied mathematics - with a keen interest to apply these techniques to financial markets and have a transformational impact on the business.
- Actively engage with senior stakeholders and leaders in Equities Cash Risk businesses along with Sales and Trading desk partners to drive the implementation of sophisticated tools / analytics and advance our risk / pricing solutions
- Develop new innovative trading strategies, as well as enhance existing trading strategies and automated solutions.
- Collaborate with various technology teams across the trading systems and data platforms
- Work closely with risk traders to manage the unwinding of risk positions and build analytics and data-driven processes that automate and optimize trading quantitatively
- Contribute from idea generation to production implementation: perform research, design prototypes, implement analytics and strategies, support their daily usage and analyze their performance
- Leverage a wide range of modern statistical techniques such as optimization, machine / reinforcement learning, neural networks, time-series forecasting, clustering methods, and dimensionality reduction methods
- Advanced degree (Masters, PhD or equivalent) in math, finance, engineering or computer science
- Reasonable experience in a related field
- Experience in implementing and maintaining quantitative solutions and trading strategies
- Excellent communication and presentation skills, especially for senior stakeholders
- Fundamental understanding of statistics, optimization, and machine learning methodologies
- Strong technical skills in software design and programming; particularly in Python and KDB
- Clearing required equities trading regulatory certifications is a plus