Quant Developer (Python) – London – Up to £200k Base + Bonus + Benefits

Hunter Bond; Greater London; On-site; GBP 90,000 - 150,000; Full time

Job summary

Hunter Bond is seeking ambitious Quant Developers for a leading systematic trading firm. You will design and implement distributed Python systems to process exabyte-scale datasets, collaborating with elite researchers to push alpha generation and trading performance.

Join a team where engineering sits at the core, with exposure to strategy and algorithm development, high-performance data platforms, and scalable infrastructure.

Qualifications

• Strong commercial Python development experience within quantitative finance or another highly complex distributed systems environment.
• Experience building large-scale distributed applications or high-performance data platforms.
• Excellent knowledge of algorithms, data structures and software architecture.
• Experience working with very large datasets and performance optimisation.
• Strong understanding of Linux environments and modern software engineering practices.
• Excellent communication skills with the ability to work alongside researchers and highly technical stakeholders.
• Computer Science, Mathematics, Physics, Engineering or similarly quantitative academic background.

Responsibilities

• Build at Extraordinary Scale – Design distributed Python systems capable of processing and analysing exabyte-scale market datasets with exceptional performance and reliability.
• Engineer Research Infrastructure – Create the platforms, tooling and data pipelines that enable world-class quantitative researchers to iterate faster and discover new sources of alpha.
• Solve Deep Technical Problems – Work on large-scale distributed computing, storage optimisation, parallel processing and high-performance data engineering.
• Collaborate with Elite Quants – Partner directly with researchers and traders to translate complex quantitative ideas into scalable production systems.
• Optimise Everything – Continuously improve latency, throughput and efficiency across every layer of the research platform.
• Own Complex Projects – Take responsibility for critical components from architecture through deployment and long-term evolution.
• Influence Technical Direction – Help shape engineering standards, platform architecture and future technology choices within a world-class engineering organisation.
• Move Closer to Alpha – As your domain knowledge develops, gain exposure to quantitative modelling, signal generation, strategy implementation and algorithm development.

Skills

Python development

Distributed systems

High-performance data processing

Linux environments

Algorithms & data structures

Communication with researchers

Education

Computer Science / Mathematics / Physics / Engineering degree

Tools

Kubernetes

Cloud infrastructure

C++

Rust

Job description

My client is one of the world's leading systematic proprietary trading firms, built around a simple philosophy: exceptional technology and exceptional people create exceptional trading performance.

Rather than treating technology as a support function, engineering sits at the very centre of the business. Every line of code directly contributes to the firm's ability to discover alpha, process unprecedented volumes of market data and execute faster than the competition.

They're now investing heavily in the next generation of their quantitative research platform, building the data and compute infrastructure that will power the firm's trading strategies for years to come.

This isn't another data engineering role. You'll be designing systems capable of handling exabyte-scale datasets, enabling researchers to interrogate enormous volumes of historical and real-time market information with extraordinary speed and efficiency.

For ambitious Quant Developers, this role also offers something increasingly rare: a genuine pathway into strategy and algorithm development, working directly alongside elite quantitative researchers as your understanding of the business grows.

Key Responsibilities

• Build at Extraordinary Scale – Design distributed Python systems capable of processing and analysing exabyte-scale market datasets with exceptional performance and reliability.
• Engineer Research Infrastructure – Create the platforms, tooling and data pipelines that enable world-class quantitative researchers to iterate faster and discover new sources of alpha.
• Solve Deep Technical Problems – Work on large-scale distributed computing, storage optimisation, parallel processing and high-performance data engineering.
• Collaborate with Elite Quants – Partner directly with researchers and traders to translate complex quantitative ideas into scalable production systems.
• Optimise Everything – Continuously improve latency, throughput and efficiency across every layer of the research platform.
• Own Complex Projects – Take responsibility for critical components from architecture through deployment and long-term evolution.
• Influence Technical Direction – Help shape engineering standards, platform architecture and future technology choices within a world-class engineering organisation.
• Move Closer to Alpha – As your domain knowledge develops, gain exposure to quantitative modelling, signal generation, strategy implementation and algorithm development.

Required Skills & Experience

• Strong commercial Python development experience within quantitative finance or another highly complex distributed systems environment - Applications from Big tech will be considered on a case by case basis depening on scope of involvement in the development of truly distributed systems.
• Experience building large-scale distributed applications or high-performance data platforms.
• Excellent knowledge of algorithms, data structures and software architecture.
• Experience working with very large datasets and performance optimisation.
• Strong understanding of Linux environments and modern software engineering practices.
• Excellent communication skills with the ability to work alongside researchers and highly technical stakeholders.
• Computer Science, Mathematics, Physics, Engineering or similarly quantitative academic background.

Nice to haves :

• Experience working within a systematic hedge fund, proprietary trading firm or quantitative investment manager.
• Exposure to distributed computing technologies and large-scale data processing.
• Knowledge of market data, financial markets or quantitative research workflows.
• Experience building research platforms or analytics infrastructure.
• Familiarity with C++, Rust or other performance-oriented languages.
• Experience with cloud infrastructure, Kubernetes or modern distributed computing environments.