CIB QR - Quantitative Research AAO Systematic Trading Researcher - Associate/Vice President
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Quantitative Research for Systematic Trading
Quantitative skills are at the core of J.P. Morgan's capabilities, contributing critically 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 equities, equity derivatives, and FX market making business. We work closely with traders to develop data-driven solutions such as algorithmic strategies (high to low frequency), trading signals, risk models, portfolio optimization, flow categorization and clustering… - and to ultimately combine them into automated trading processes.
We are seeking individuals passionate in areas such as electronic trading, 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. Roles and responsibilities include
- Work closely with trading to build analytics (single instrument and portfolio) and data-driven processes that automate and optimize trading quantitatively, with special focus on delta one synthetic index trading.
- Contribute from idea generation to production implementation: perform research, design prototype, implement analytics and strategies, support their daily usage and analyse their performance
- Develop pricing models for client activities taking into account profiles, quantitative features, and historic behaviour using statistics, machine learning or heuristics.
- Work with the business to centralize risk and devise hedging strategies accordingly.
The ideal candidate will have:
- Strong graduate degree in a quantitative field (Mathematics, Physics, Statistics, Economics, or similar); PhD degree preferred
- Exceptional analytical, quantitative and problem-solving skills, as well as the ability to communicate complex research in a clear and precise manner
- Excellent communication skills, both oral and written
- Entrepreneurial spirit and passion for spreading a culture of change towards data-driven decision making
- Strong software design and development skills using Python, C++ or Java
- Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources, understanding and working knowledge of trading data and how to manage it, KDB/q experience is a plus
- 1 to 3 years' experience in finance: electronic trading, portfolio analytics (risk modelling, portfolio optimization, synthetic trading, ETF trading), trading strategies (high to low frequency: market making, statistical arbitrage, option trading…), derivatives pricing and risk management