Front Office Python Developer – Low-Latency Trading Systems

NLS Executive Search; Hong Kong; On-site; HKD 800,000 - 1,600,000; Full time

Benefits offered by this job

Office in Central, Hong Kong

Discretionary bonus potential

Job summary

Our client is a reputable fund with offices in Hong Kong and Singapore, seeking a Front Office Python Developer to design, develop, and maintain high-performance trading systems that support front office operations.

You will collaborate with traders, quants, and other stakeholders to implement algorithmic trading strategies, integrate data feeds, and optimize for low-latency execution in a fast-paced environment.

Qualifications

• Bachelor's degree in a related field.
• Strong Python programming for front office finance.
• Knowledge of financial markets, trading workflows, and strategies.
• Experience with algorithmic trading and quantitative analysis.
• Experience with data feeds and trade execution systems.
• Excellent problem-solving and collaboration skills.
• Previous front office hedge fund experience is desirable.

Responsibilities

• Design, develop, and maintain high-performance Python trading systems.
• Collaborate with traders and researchers to gather requirements.
• Implement algorithmic trading strategies and models.
• Integrate third-party data feeds and APIs.
• Ensure low-latency execution and high throughput.
• Test, debug, and validate trading systems.
• Deploy systems with production readiness and monitoring.
• Document architecture and procedures.

Skills

Python programming

Front office trading

Quantitative finance

Real-time data

Low-latency

Education

Bachelor's degree in CS/Engineering/Math

Tools

Market data feeds

Order management systems

Execution platforms

Quant libraries

Job description

Our client is a reputable fund with offices in Hong Kong and Singapore, seeking a Front Office Python Developer to design, develop, and maintain high-performance trading systems that support front office operations.

You will collaborate with traders, quants, and other stakeholders to implement algorithmic trading strategies, integrate data feeds, and optimize for low-latency execution in a fast-paced environment.