Rates Algo Trading Strategist (Associate/VP)

Morgan Stanley; New York (NY); On-site; USD 150,000 - 250,000; Full time

Job summary

Morgan Stanley's US E-Swaps team seeks a quantitative strategist focused on algorithmic market making to build and operate automated trading strategies that support trading performance.

The role blends research, hands-on development, and live trading collaboration with traders, sales, fellow strats, and technology. Strong coding, numerical modeling, and data analysis are essential.

Expected to contribute to pricing, hedging, and risk management, with impact on PnL and market share.

Qualifications

• 4+ years of experience in a quantitative role, ideally within trading, electronic market making, algorithmic trading, or a front‑office environment.
• Bachelor’s degree or higher in CS, Engineering, Math, Physics, Financial Engineering, or related quantitative field.
• Strong programming skills in Python and working understanding of software development lifecycle and system design.
• Experience working with large or high‑frequency market and trading datasets using KDB/q.
• Strong analytical and problem‑solving skills, with sharp attention to detail and a proactive mindset.

Responsibilities

• Lead initiatives across the full lifecycle of electronic and algorithmic market making, from research and modeling to back‑testing, deployment, live monitoring, and performance optimization.
• Use quantitative methods, including machine learning and statistical modeling, to build, improve, and operate automated trading strategies across pricing, hedging, execution, and risk management.
• Analyze market data, trading behavior, client flow, and execution patterns to identify signals and monetizable opportunities, then translate those insights into practical enhancements to live trading algorithms.
• Monitor algo performance and market conditions to help ensure strategies respond effectively to changing market dynamics.
• Partner with trading and sales to identify opportunities that improve PnL, market share, client coverage, and execution efficiency.
• Collaborate with technology teams to develop solutions that are robust, scalable, and production‑ready.

Skills

Python

KDB/q

Analytical thinking

Front-office experience

Education

Bachelor’s degree or higher in a quantitative field

Tools

KDB/q

Job description

Morgan Stanley's US E-Swaps team seeks a quantitative strategist focused on algorithmic market making to build and operate automated trading strategies that support trading performance.

The role blends research, hands-on development, and live trading collaboration with traders, sales, fellow strats, and technology. Strong coding, numerical modeling, and data analysis are essential.

Expected to contribute to pricing, hedging, and risk management, with impact on PnL and market share.