Role OverviewThe US E-Swaps team builds advanced models and systems that power trading in USD interest rate swaps. As a quantitative strategist focused on algorithmic market making, you will help build, improve, and operate automated trading strategies that support the performance of the business.
This role combines quantitative research, hands-on development, and close engagement with live trading systems. You will analyze market data, identify signals and monetizable opportunities, and translate those insights into enhancements across pricing, hedging, execution, and risk management. Your work will influence PnL, market share, client coverage, execution efficiency, and how the algo responds to changing market conditions.
This is a high-impact front-office role with strong visibility. You will collaborate closely with trading, sales, fellow strats, and technology teams while contributing to the desk's trading performance and automated market-making capabilities.
Key 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.
Required 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 Computer Science, Engineering, Mathematics, Physics, Financial Engineering, or a 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.
Preferred Qualifications - Familiarity with Java or other object-oriented programming languages.
- Experience working on automated market-making strategies, including pricing, hedging, execution, or risk-management logic.
- Experience with rates product including swaps, USTs, bond/rate futures, and familiarity with pricing and risk calculation.
Ideal Candidate Profile The ideal candidate is a hands-on quant strategist who combines strong technical skills with a rigorous analytical approach and takes ownership from idea generation and design through implementation, testing, and ongoing improvement, with a focus on practical business impact.
Expected base pay rates for the role will be between
$150,000 - $200,000 per year for Associate and between
$225,000 - $250,000 for
Vice President at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
