CLSA
From CLSA's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
Position Description
The Algorithmic Trading team is looking for an Execution Quant to join our Hong Kong development centre.
Our trading platform is purely developed in-house; the successful candidate will work closely with the Electronic Execution desk, Equity Traders and our global team of Quants and Technologists to deliver high quality, cutting-edge quantitative execution solutions for our clients.
The ideal candidate is passionate about technology. The successful candidate will drive the improvement of our data, quant research, model calibration and backtesting infrastructure as well as carry out custom client-driven execution research, provide quantitative advisory services to our clients, research market microstructure and trading models and help implement them.
The successful candidate is likely to gain further exposure to cutting-edge technologies as well as in-depth knowledge of quantitative algorithmic trading.
Contribute to the development and enhancement of the electronic trading product throughout the entire development cycle.
Conduct advanced research into trading signals, optimal scheduling, and order placement strategies.
Research market microstructure and perform custom execution research tailored to client needs.
Provide quantitative advisory services to support client trading strategies.
Align the strategic direction of algorithmic products with overall business goals and client expectations.
Optimize algorithm wheel configurations to improve trading efficiency.
Data mine trading exhaust to identify insights and enhance trading algorithms.
Collaborate with cross-functional teams to implement research findings and improve trading performance
Bachelor Degree or above in Mathematics, Physics, Engineering, Computer Science or any quantitative studies
Min. 3 years’ experience as Python Quant Developer preferred
Strong programming skills, at the minimum in Python, and a proven interest in computer science
Strong problem-solving and analytical skills
Strong data pipelining and analysis skills
Strong communication and interpersonal skills
Strong team player and open to new ideas with ability to pay attention to details even under pressure
Self-motivated, keen learner and strong sense of ownership and accountability
Ability to code in q/kdb+
Development experience in C# or other object oriented programming languages
Experience in applying statistical and machine learning techniques to real-life problems
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