Quantitative Trading & Research - Mid-Frequency Trading Strategies - Vice President

JPMorganChase is forming a Mid-Frequency Strategies team focused on the research, development, and execution of systematic trading strategies.

The group operates at the intersection of quantitative research and trading, developing strategies that span alpha generation, portfolio construction, risk management, and execution infrastructure - with statistical analysis and machine learning at the core.

You will work alongside experienced traders, researchers, and technologists in a collaborative environment where research directly drives live trading decisions.

Job Summary

As a Vice President within the Mid-Frequency Trading Strategies team, you will play a central role in designing and implementing JPMorgan Chase's mid-frequency trading framework.

You will be responsible for the full lifecycle of strategy development - from ideation and statistical

research through production deployment and ongoing performance monitoring.

This is a highly quantitative role requiring deep expertise in statistical modelling, machine learning, and financial markets, and is suited to someone who thrives at the boundary of research and live trading.

Job Responsibilities


* Improve the mid-frequency trading framework, including the architecture for signal generation, alpha combination, portfolio optimization, and execution logic, ensuring the platform is robust, scalable, and production-ready.


* Research and develop proprietary trading strategies using advanced statistical modelling and machine learning techniques, with a focus on identifying persistent, risk-adjusted alpha signals across relevant asset classes.


* Apply machine learning methodologies - including supervised and unsupervised learning, reinforcement learning, and time-series modelling - to extract predictive signals from large, complex datasets including market microstructure, alternative data, and macroeconomic indicators.


* Own the end-to-end research process, from hypothesis generation and backtesting through to live deployment, with rigorous statistical validation to guard against overfitting and data snooping biases.


* Develop and maintain production-grade implementations of trading strategies and supporting infrastructure, working with technology partners to integrate models into the live trading environment.


* Monitor live strategy performance, carry out PnL attribution, identify regime changes, and continuously iterate on models to maintain and improve P&L generation.

Required Qualifications, Capabilities, and Skills


* Master's degree in a quantitative STEM discipline such as Statistics,


* Mathematics, Physics, Computer Science, or Financial Engineering


* Minimum 5 years of experience in quantitative trading, quantitative research, or systematic strategy development role, ideally within a prop trading environment, hedge fund, or sell-side systematic trading desk


* Demonstrable expertise in statistical modelling, including time-series analysis, ...