Quantitative Strategist Electronic Trading

NexusSearch International Limited; Hong Kong; On-site; HKD 781,200 - 892,800; Full time

Job summary

A leading financial services recruitment company in Hong Kong is seeking a Quantitative Strategist for Electronic Trading. The candidate will enhance the firm's automated trading platform, identify inefficiencies, and perform transaction cost analysis. Ideal candidates have at least 4 years of relevant experience, strong programming skills in languages like Python or C++, and knowledge of equity markets. This role offers a competitive budget of HKD 70-80K per month, plus bonuses.

Qualifications

• 4 years of experience in electronic trading, quant research, or execution analytics.
• Strong programming skills and experience with statistical modeling/machine learning.
• Deep knowledge of equity markets.

Responsibilities

• Enhance the firm’s automated trading platform.
• Identify inefficiencies and drive data-driven improvements.
• Lead transaction cost analysis and provide insights.

Skills

Python

C++

Java

Statistical modeling

Machine learning

SQL

NoSQL

Education

Degree in Financial Engineering, Data Science, or related field

Job description

Quantitative Strategist Electronic Trading

About the job Quantitative Strategist Electronic Trading

Department: Equity Electronic Trading

Budget: HKD 70-80K/month + bonus

Key Responsibilities:

• Enhance the firms automated trading platform by maintaining and optimizing predictive models for algorithmic trading.
• Proactively identify inefficiencies and drive data-driven improvements to execution performance.
• Lead transaction cost analysis (TCA), providing clients and internal stakeholders with actionable insights on execution quality and trends.
• Produce research on market microstructure, regulatory impacts, and other trading-related topics to inform strategy.

Qualifications:

• 4 years of experience in electronic trading, quant research, or execution analytics.
• Strong programming skills (Python, C++, Java, or similar) and experience with statistical modeling/machine learning.
• Deep knowledge of equity markets, including DMA, algos, and TCA.
• Proficiency in SQL/NoSQL databases and handling large datasets.
• Background in financial engineering, data science, or a related quantitative field preferred.
• Self-motivated team player with strong communication skills and high ethical standards.