Stanford Black Limited
Quantitative Developer
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Python Quant Developer – Highly Successful Systematic Hedge Fund | London, United Kingdom
(OPEN TO PROFILES OUTSIDE OF FINANCE)
The Quant Developer will join a highly collaborative Quantitative Development team, partnering directly with quantitative researchers to design, build, and optimise the software that powers research, modelling, and systematic trading across global financial markets.
This role sits at the intersection of software engineering and quantitative research, giving you the opportunity to build scalable research infrastructure, develop high-performance data platforms, and work on technically challenging distributed systems.
Company Highlights:
- Global systematic Hedge Fund with offices across London, New York, and Singapore
- Technology-first, research-driven environment where software is a core competitive advantage
- Engineers work directly alongside quantitative researchers with real ownership and influence
- Significant investment in proprietary technology, high-performance computing, and large-scale research infrastructure
- Collaborative culture with close interaction between engineering, research, and trading teams
- Opportunity to solve complex distributed systems and data engineering challenges at scale
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Key Responsibilities:
- Partner with quantitative researchers to design and build scalable research and trading platforms
- Develop robust Python applications that support quantitative modelling and live trading workflows
- Build efficient distributed systems for processing, storing, and analysing large volumes of data
- Take ownership of projects throughout the full software development lifecycle
- Collaborate with engineering teams globally to build reusable frameworks and shared tooling
- Improve the performance, scalability, and reliability of research infrastructure
- Design software solutions that can support multiple asset classes and quantitative strategies
- Contribute to engineering best practices, testing, automation, and code quality
- Drive AI/ML engineering efforts
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Tech Stack:
- Python
- Distributed systems and backend engineering
- Large-scale data processing and analytics
- SQL and database technologies
- Git and modern version control
- Logging, monitoring, and observability tooling
- Agile software development methodologies
Ideal Candidate Profile:
- 2+ years' commercial experience developing software in Python
- Degree in Computer Science, Mathematics, Physics, Engineering, or another STEM discipline
- Experience building highly scalable or distributed backend systems
- Background in fintech, big tech, SaaS, cloud infrastructure, data platforms, AI/ML, or other engineering-led environments welcomed
- Experience working with large datasets, data pipelines, or high-performance applications is advantageous
- Strong problem-solving and analytical skills
- Excellent communication skills and the ability to work closely with engineers and researchers
- An interest in quantitative finance and systematic trading, with a willingness to learn the domain
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