The Quantitative Developer (QD) has several core work domains:

1. Machine Learning (ML) Related Tasks:

* Establish the team's proprietary ML pipeline, encompassing everything from data sampling to reporting * Implement the team's proprietary ML models. * Enhance existing ML packages with new features. * Numerically optimize ML algorithms to boost performance.

1. Microstructures Research: * Develop tools for researching microstructure features. * Collaborate with quant researchers to generate microstructure features.
2. Portfolio Optimization and Execution: * Design portfolio optimizers for efficient asset allocation. * Implement execution strategies utilizing the firm's infrastructure platform. * Create execution simulators to streamline trading operations.
3. Data Pipeline, Computing Farm, and General IT Management: * Work alongside the firm's data team to onboard market and alternative data. * Maintain the computing farm to ensure optimal performance. * Oversee general storage and IT management responsibilities.

Among these domains, areas 1, 2, and 3 are of paramount importance. The QD will primarily tackle problems within these areas.

The ideal candidate should demonstrate exceptional learning abilities and strong software development skills. They must demonstrate a passion for solving complex problems by writing efficient software composed of effective modules. While prior experience in finance is not essential, candidates should have a proven track record of resolving challenging problems through coding. It would be highly beneficial if candidates have over two years of experience working with industrial-grade codebases using compiled languages such as C++, Java, or Go.

For a confidential discussion, please send an email with your updated resume or LinkedIn URL, with contact details in the first instance by clicking Apply Now to apply job.

Contact the retained consultants, Edward Chen or Richard Liu on +852 2523 9955

Harbridge Partners Limited

Employment Agency License: 75427

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