Credit Automated Trading Strat / Quant Researcher - Fixed Income - Vice President

Morgan Stanley•New York, NY

1d•Onsite

About The Position

The Credit Automated Trading team builds the models, systems and AI-driven tools that underpin our highly successful automated trading business. This business covers a range of global products from corporate bonds and portfolio trades to fixed income ETFs and credit futures. We are looking for a researcher to work with us at the frontier of algorithmic credit trading, developing new ways to manage risk, predict liquidity, and trade at scale. As a strategist on the team, you will do far more than research in isolation. You will design, develop, and deploy automated trading solutions. You will work closely with traders and technology partners, contribute directly to desk performance, and take ideas from concept to production. You will have access to a set of leading AI tools to assist you in your pursuit of ever better models. Research is essential, but delivery is what defines success. We are looking for someone creative, driven, and self-directed. This means taking ownership, challenging assumptions, and pushing ideas until they are fully implemented. We value people who are practical about using AI and modern tools to move faster and make better decisions. Success is measured by improvements in model performance, pricing accuracy, and impact on trading outcomes. If you enjoy solving hard modelling problems, working with imperfect data, and seeing your work deployed, you will feel at home.

Requirements

2–5 years of experience in a quantitative role.
Advanced degree (PhD, Master or equivalent) in quantitative fields such as math, statistics.
Experience applying modern technologies, including AI, to solve quantitative and modelling problems.
Solid understanding of probability, statistics, machine learning, and optimization.
Proficiency in Python.
Basic understanding of financial markets.
Able to explain a model to a trader, defend it to validators, and discuss implementation details with technology.
Comfortable working independently while managing multiple projects simultaneously.
Self-motivation, rigor, and tenacity.

Nice To Haves

Familiarity with Q/Kdb+, Scala or Java is beneficial.
Knowledge of fixed income is preferred.

Responsibilities

Use modern analytical tools and LLMs to improve models, speed up development, and idea generation across the desk.
Develop and improve real-time pricing models for tens of thousands of corporate and sovereign bonds with limited and noisy input of market data.
Identify patterns and factors driving trading flow, liquidity and market behavior and translate them into actionable signals.
Own initiatives across the full lifecycle of electronic trading from research, modelling and back-testing to deployment and continuous performance improvement.
Partner closely with bookrunners, strats and technology to deliver solutions.
Enhance our back-testing and research framework to accelerate idea generation.