Quantitative Researcher / Senior Quantitative Researcher (quantitative developer)

Bank of China (Hong Kong) Limited; Hong Kong Island; On-site; HKD 600,000 - 800,000; Full time

Job summary

A financial institution is seeking a Quantitative Researcher / Senior Quantitative Researcher to enhance insights through algorithmic trading and execution systems. Responsibilities include developing scalable designs, implementing advanced algorithms, and applying machine learning and AI technologies. The ideal candidate will possess a strong educational background in relevant fields and have at least 2 years of hands-on experience.

Qualifications

• 2+ years experience in relevant work is a plus.
• Hands-on experience in quantitative trading and/or market analysis.
• Strong understanding of market microstructure.

Responsibilities

• Design, develop, and maintain core components of Algo trading and Orders execution systems.
• Implement robust algorithms for various trading strategies.
• Leverage machine learning and AI techniques to improve trading signals and execution solutions.

Skills

Programming skills

Machine Learning

Deep Learning

Education

Bachelor, Master or PHD in CS, QuantFinance, Math, Physics

Tools

PyTorch

TensorFlow

Scikit-learn

XGBoost

LightGBM

Job description

Quantitative Researcher / Senior Quantitative Researcher (quantitative developer)

Apply Now Job No.: 498468
Employment Type: Full time
Departments: Global Markets
Job Functions: FinTech

Responsibilities:

• Design, develop, and maintain core components of Algo trading and Orders execution systems, ensuring high scalability, reliability, and performance.
Collaborate closely with quantitative researchers, traders, and project managers to deliver innovative solutions that enhance trading and execution workflows. Implement robust algorithms to support a variety of trading strategies, such as market making and alpha capture. Lead or actively contribute to project management, ensuring timely delivery of high-quality solutions in a fast-paced environment. Leverage advanced machine learning and deep learning techniques to improve trading signals, risk management, and execution solutions. Explore and apply large language models (LLMs) and generative AI technologies (e.g., Qwen, Deepseek) to drive innovation in trading research and automation, including Retrieval-Augmented Generation (RAG) solutions. Stay abreast of the latest advancements in quantitative finance, AI, and machine learning, incorporating relevant research into practical applications.

Requirements:

Bachelor, Master or PHD in CS,QuantFinance, Math, Physics or other releated disciplines. 2+ years+ experience in relevant work as a plus. Strong programming skills with experience in designing and building scalable trading or risk systems. Hands-on experience in quantitative trading and/or market analysis, with a deep understanding of market microstructure. Proven track record in delivering large-scale, production-level projects within complex environments or leading financial institutions. Practical experience with major machine learning and deep learning frameworks, including but not limited to,PyTorch,TensorFlow, Scikit-learn,XGBoost / LightGBM Experience with LLMs and related frameworks/packages, such as: Hugging Face Transformers, LangChain,Retrieval-Augmented Generation (RAG), Deepseek/Qwen API, Dify, or similar Ability to integrate and deploy deep learning and LLM models in production environments, including model serving, API integration, and monitoring. Excellent communication and teamwork skills, with the ability to work effectively in cross-functional teams. Strong interest and hands-on experience in applying LLMs and generative AI to solve real-world problems in finance, such as signal extraction, alpha research, knowledge management, or workflow automation.

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