Quantitative Researcher

Albert Bow; Greater London; On-site; GBP 250,000 - 500,000; Full time

Job summary

Albert Bow in London is seeking a Quantitative Researcher to advance research into trading strategies and market microstructure. You will develop strategies, backtest rigorously, and push production-ready code in a collaborative team.

The role emphasizes strong Python programming with experience in compiled languages and a passion for data-driven insight. Competitive compensation includes significant upside in a fast-growing crypto market.

Qualifications

• Advanced degree in a quantitative field (MSc/PhD).
• Strong research skills applying mathematical tools to real problems.
• ≈3+ years of empirical data analysis in a scientific context.
• Proficiency in Python and at least one compiled language (Rust/C++/Go).
• Familiar with Linux/Unix, AWS, Git and Docker.
• Exposure to market microstructure or trading research desired.
• Entrepreneurial mindset and proactive problem-solver.

Responsibilities

• Research and implement trading and pricing strategies, including high-frequency approaches.
• Analyse large datasets to discover statistical trading opportunities and validate models.
• Develop and improve simulation/backtesting frameworks to align with live performance.
• Translate mathematical models into production code with engineers.

Skills

Python

Rust

C++

Go

Linux/Unix

AWS

Git

Low-latency systems

Education

MSc/PhD in Mathematics/Statistics/Physics/CS/Engineering

Tools

Docker

Job description

Quantitative Researcher | HFT | Crypto | London £250k + PnL

We are a fast-growing, venture-backed technology firm focused on building trading and liquidity solutions across multiple markets. We operate in a collaborative, flat start up environment that values technical excellence, initiative, and practical impact.

Role overview

We are looking for a Quantitative Researcher with strong analytical and programming skills and a passion for systematic research and market microstructure. You will contribute to the development of trading strategies and research infrastructure, working closely with a small technical team. The role offers early responsibility and the opportunity to shape long-term research direction.

Key responsibilities

• Research and implement trading and pricing strategies, including high-frequency approaches
• Analyse large datasets to discover statistical trading opportunities and validate models
• Develop and improve simulation and backtesting frameworks to better match live performance
• Translate mathematical models into robust production code in collaboration with engineers

Required qualifications & skills

• Advanced degree (MSc/PhD) in Mathematics, Statistics, Physics, Computer Science, Engineering, or a similar quantitative field
• Strong research skills and experience applying mathematical and statistical tools to real-world problems
• ~3+ years of hands-on experience analysing empirical data in a scientific manner
• Proficient in Python; strong experience in at least one compiled language (Rust, C++, Go, etc.)
• Comfortable with Linux/Unix, cloud environments (e.g., AWS), Git and containerisation (Docker)
• Prior exposure to market microstructure or trading research is preferred
• Entrepreneurial mindset, proactive problem-solver, and effective collaborator
• Experience building or optimising low-latency systems
• Familiarity with simulation frameworks and performance measurement in production

What we offer!

• Fast-paced, collaborative environment with ownership of research through deployment.
• Access to high-quality market data and state-of-the-art infrastructure.