FICC Quant Execution Trader: Algo & Automation

Morgan McKinley; Hong Kong; On-site; HKD 700,000 - 1,000,000; Full time

Job summary

Morgan McKinley is seeking a Quant Execution Trader for its FICC trading desk. The role focuses on designing, deploying, and managing quantitative execution algorithms, automated pricing frameworks, and liquidity-seeking models across FICC products.

Key responsibilities include algorithmic execution, QTA/TCA, and collaboration with researchers and tech teams to implement systematic trading logic with real-time risk controls.

Qualifications

• Advanced degree in quantitative fields (e.g., Quantitative Finance, Mathematics, CS, Physics, or Engineering).
• 2+ years in quantitative execution, systematic market making, or algorithmic trading within FICC.
• Proficiency in Python and C++ for model building and data manipulation.
• Experience with SQL and trading tool development.
• Strong understanding of FICC market microstructure and electronic trading protocols.

Responsibilities

• Algorithmic Execution & Order Routing: optimize real-time execution algorithms (TWAP, VWAP, IS) and smart order routing across electronic FICC venues.
• Quantitative Analysis & TCA: conduct microstructure studies and high-frequency data analysis to minimize market impact.
• Strategy & Model Development: collaborate to design, backtest, and implement systematic trading logic and risk controls.
• Desk Flow & Risk Management: monitor live order execution, manage intraday inventory and exposure.
• Automation & Infrastructure: build Python-based analytics tools, dashboards, and data pipelines to automate workflows.

Skills

Python

C++

SQL

Education

Advanced degree in quantitative fields

Job description

Morgan McKinley is seeking a Quant Execution Trader for its FICC trading desk. The role focuses on designing, deploying, and managing quantitative execution algorithms, automated pricing frameworks, and liquidity-seeking models across FICC products.

Key responsibilities include algorithmic execution, QTA/TCA, and collaboration with researchers and tech teams to implement systematic trading logic with real-time risk controls.