Quant Software Engineer

Harrington Starr; Greater London; Hybrid; GBP 120,000 - 150,000; Full time

Job summary

Harrington Starr, a London-based hedge fund, is seeking a Quantitative Developer to bridge quant research and software engineering. You will help turn hypotheses into production trading systems while collaborating with senior researchers and investment professionals.

The role focuses on Python-based research, backtesting, large data handling, and building reusable pipelines in a hybrid London setting.

Qualifications

• Strong Python development skills.
• Experience with quantitative research and backtesting.
• Strong understanding of statistics and large datasets.
• Strong software engineering fundamentals.
• Experience building reusable research/data pipelines.
• Academic background in CS, Math, Stats, Physics, Engineering or similar.
• Genuine interest in financial markets and quantitative investing.
• Ability to take ambiguous problems and independently determine solutions.

Responsibilities

• Researching and evaluating quantitative trading signals
• Building backtesting and simulation infrastructure
• Developing production-quality Python research and trading systems
• Building and maintaining large financial and alternative datasets
• Developing reusable research pipelines and analytical tooling
• Working on portfolio construction, position sizing and risk
• Monitoring live signals and investigating performance
• Using AI agents and LLMs within quantitative research and automation
• Working directly with Quant Researchers, Portfolio Managers and the wider investment team

Skills

Python

Quantitative research

Backtesting

Statistics

Software engineering

Research pipelines

Academic background

Financial markets

Education

CS/Math/Stats/Physics/Engineering degree

Tools

Kubernetes

SQL

Cloud platforms

Workflow orchestration

Distributed data processing

AI/LLM tooling

Job description

Quantitative Developer – Hedge Fund

London | Hybrid | Python | Quant Research | Systematic Trading

I'm working with an established London-based hedge fund that is building a next-generation, AI-enabled quantitative equity investment platform.

They're looking for a Quantitative Developer to join the founding team, sitting directly between quantitative research and software engineering. You'll work closely with senior researchers and investment professionals, taking ideas from initial hypothesis through research, backtesting and ultimately into production trading systems.

What you'll be doing

• Researching and evaluating quantitative trading signals


• Building backtesting and simulation infrastructure


• Developing production-quality Python research and trading systems


• Building and maintaining large financial and alternative datasets


• Developing reusable research pipelines and analytical tooling


• Working on portfolio construction, position sizing and risk


• Monitoring live signals and investigating performance


• Using AI agents and LLMs within quantitative research and automation


• Working directly with Quant Researchers, Portfolio Managers and the wider investment team

What we're looking for

• Strong Python development skills


• Experience with quantitative research and backtesting


• Strong understanding of statistics and working with large datasets


• Strong software engineering fundamentals


• Experience building reusable research/data pipelines


• Strong academic background in Computer Science, Mathematics, Statistics, Physics, Engineering or similar


• Genuine interest in financial markets and quantitative investing


• Ability to take ambiguous problems and independently determine how to solve them

Experience within a hedge fund, asset manager, prop trading or systematic investment environment is advantageous, as is exposure to cloud, Kubernetes, workflow orchestration, SQL, distributed data processing and AI/LLM tooling.

£120,000+ base + bonus | London

If you're a strong Python/Quant Developer who wants significant ownership and the opportunity to help build a quantitative investment platform from an early stage.