CIB QR – Quantitative Research, Systematic Trading – Automated Trading Strategies (ATS) – Associate

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 Interest Rates, FX and Commodities 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, machine learning, reinforcement learning, deep learning,  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 and data-driven processes that automate and optimize trading quantitatively

Contribute from idea generation to production implementation: perform research, design prototype, implement analytics and strategies, support their daily usage and analyse their performance

Leverage on a wide range of modern techniques such as optimization (linear, quadratic, conic…), reinforcement learning, neural networks, time-series forecasting, clustering methods, dimensionality reduction methods (PCA, Kernel methods, factor models…)
Qualifications
 
The ideal candidate will have:

Earned a MS, PhD or equivalent degree program in machine learning, mathematics, statistics, econometrics, financial engineering, computer science, operational research, physics or chemistry

Publications or experience in applied mathematics, statistics, optimization, computer science or data science (machine learning, reinforcement learning, computer vision, NLP…)

Exceptional analytical, quantitative and problem-solving skills, as well as the ability to communicate complex research in a clear and precise manner

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. KDB is extremely advantageous

Ability to manipulate and analyze complex, large scale, high-dimensionality data from varying sources (use of TensorFlow and other standard machine learning packages)

Experience in finance: electronic trading, portfolio analytics (risk modelling, portfolio optimization), trading strategies (high to low frequency: market making, statistical arbitrage, option trading…), derivatives pricing and risk management

Autonomy, excellent communication, strong motivation and interest in electronic trading and equity markets 
About J.P. Morgan’s Corporate & Investment Bank:
 
J.P. Morgan’s Corporate & Investment Bank is a global leader across banking, markets and investor services. The world’s most important corporations, governments and institutions entrust us with their business in more than 100 countries. With $18 trillion of assets under custody and $393 billion in deposits, the Corporate & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.  Further information about J.P. Morgan is available at www.jpmorgan.com.
 
JPMorgan Chase & Co. offers an exceptional benefits program and a highly competitive compensation package. JPMorgan Chase & Co. is an Equal Opportunity Employer.