Quantitative Researcher - Trading Team
Quantitative Research · London · Full-time · On-site
Annual base salary: £220,000 – £225,000 GBP
Role description
Westren Capital is a research-driven quantitative investment firm focused on systematic strategies across global markets. We hire from Mathematics, Physics, Computer Science and related fields, not for credentials, but for the ability to reason clearly under uncertainty and build things that work in production.
Our work sits at the intersection of statistical modelling, market microstructure, and engineering. The aim is straightforward, if not easy: extract durable signals from noisy data and convert them into scalable, risk-aware strategies. That requires intellectual honesty, a tolerance for ambiguity, and a willingness to discard ideas that do not survive contact with reality.
We operate in small, highly collaborative teams where research, engineering, and trading are tightly coupled. Outcomes matter. Not narratives, not backtests that look good in isolation, but strategies that hold up live. Compensation and progression reflect that directly.
Beyond trading, we invest in building internal tools, data infrastructure, and research workflows that compound over time. The edge is rarely a single idea; it is the system that produces and evolves ideas faster than others.
Responsibilities:
Develop and test alpha signals across liquid markets, with a focus on robustness rather than backtest aesthetics
Work with large, messy datasets and turn them into something usable without fooling yourself in the process
Build research pipelines that are fast, reproducible, and resistant to the usual traps (lookahead, leakage, overfitting)
Collaborate with engineers to move ideas into production without breaking them in the process
Study market microstructure and execution behaviour, not as theory but as something that directly impacts returns
Monitor live strategies and investigate performance drift, which happens more often than people admit
Requirements
Requirements
Strong problem-solving ability and independent thinking; comfort working in areas where the answer is not obvious and often wrong the first few times
Experience developing quantitative trading strategies is valued, but not required; evidence of rigorous, applied research matters more
Solid grounding in statistical modelling and forecasting techniques; familiarity with machine learning methods such as regression, tree-based models, or neural networks
Degree (Bachelor’s, Master’s, or PhD) in Mathematics, Statistics, Physics, Computer Science, or a related field
Strong programming skills in Python; experience with C++ and working in a Linux environment is a plus
Ability to work in a collaborative, high-performance environment where feedback is direct and iteration cycles are fast