Associate Quant Strategies — Automated Trading & Tech

HSBC; Greater London; On-site; GBP 120,000 - 190,000; Full time

Job summary

HSBC is seeking a highly qualified quantitative researcher to define, develop and monitor automated trading algorithms within the eRisk team in London. You will work with modern statistical techniques and production-grade systems to support liquidity provision and risk management in a fast-paced environment.

Applicants should have a PhD in a quantitative field, strong experience in systematic trading or algorithmic market making, and proven ability to translate research into scalable solutions

Qualifications

• PhD in a quantitative discipline.
• Experience in major electronic trading, especially systematic trading or market making.
• Deep understanding of market microstructure and algorithmic trading fundamentals.
• Statistical analysis skills and research practices to develop and validate models.
• Publications or demonstrable contributions to quantitative research.

Responsibilities

• Own definition, development, implementation, maintenance and monitoring of automated trading algorithms and strategies.
• Deliver milestones in a fast-paced front office environment, balancing research, build and production work.
• Apply Python, R or Matlab for analysis; use SQL for data access.
• Implement production-grade components using Java to support deployment.
• Evaluate market microstructure and algorithmic trading fundamentals across FX, STIR and other products.
• Collaborate with technology teams to improve systems and operational robustness.
• Understand and manage key risks within the first line of defence and risk framework.
• Build relationships with clients and stakeholders, communicating outcomes clearly.

Skills

Statistical analysis

Market microstructure understanding

Research publications

Communication with clients

AI/ML exposure

Education

PhD in a quantitative discipline

Tools

Python

R

Matlab

SQL

Java

Job description

HSBC is seeking a highly qualified quantitative researcher to define, develop and monitor automated trading algorithms within the eRisk team in London. You will work with modern statistical techniques and production-grade systems to support liquidity provision and risk management in a fast-paced environment.

Applicants should have a PhD in a quantitative field, strong experience in systematic trading or algorithmic market making, and proven ability to translate research into scalable solutions