Quantitative Researcher, Live Alpha Signals

Westren Capital; Greater London; Hybrid; GBP 60,000 - 180,000; Full time

Job summary

Westren Capital, a London-based proprietary trading firm, seeks researchers who can transform messy data into robust trading signals. You will work at the intersection of statistics, machine learning, and market microstructure, building strategies that operate in live markets.

The team is small and highly collaborative, valuing rigorous applied research over backtests. Candidates with strong Python and Linux experience, and a track record in quantitative research, will fit well in this

Qualifications

• Strong problem-solving ability and independent thinking; comfort with uncertain, non-obvious problems
• Experience developing quantitative trading strategies valued; evidence of rigorous applied research matters
• Solid grounding in statistical modelling and forecasting; familiarity with regression, tree-based models, or neural networks

Responsibilities

• Develop and test alpha signals across liquid markets focusing on robustness
• Work with large, messy datasets and turn them into usable insights
• Build fast, reproducible research pipelines resisting leakage and overfitting
• Collaborate with engineers to move ideas into production
• Study market microstructure and execution behaviour to improve returns
• Monitor live strategies and investigate performance drift

Skills

Problem solving

Independent thinking

Python programming

C++ experience

Linux experience

Machine learning

Statistical modelling

Forecasting techniques

Quantitative trading

Team collaboration

Education

Bachelor’s/Master’s/PhD in Mathematics/Statistics/Physics/CS

Tools

Python

C++

Linux

Git

Job description

Westren Capital, a London-based proprietary trading firm, seeks researchers who can transform messy data into robust trading signals. You will work at the intersection of statistics, machine learning, and market microstructure, building strategies that operate in live markets.

The team is small and highly collaborative, valuing rigorous applied research over backtests. Candidates with strong Python and Linux experience, and a track record in quantitative research, will fit well in this