Quant Researcher (MFT Focus) - Trading Team
Quantitative Research · London · Full-time · On-site
Annual base salary: £210,000 – £230,000 GBP
Research and build medium-frequency systematic trading strategies across digital asset markets.
Role description
Westren Capital is a London-based proprietary trading firm specialising in digital asset markets. We develop systematic trading strategies grounded in market microstructure across global venues, with this role focused specifically on medium-frequency, multi-day to multi-week holding period strategies.
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.
Responsibilities
Research and build medium-frequency trading strategies, where signal decay is measured in days, not microseconds, and the traps are different from HFT but no less real
Work with cross-sectional and time-series data across digital asset markets to identify persistent, economically grounded signals
Build portfolio construction and risk allocation frameworks suited to multi-day holding periods and correlated crypto exposures
Stress-test strategies against regime shifts, liquidity crunches, and the tail events MFT books are more exposed to than HFT ones
Collaborate with execution and infrastructure teams so strategies that look good on paper actually get filled at the prices the backtest assumed
Monitor live books for drift and slow decay, the kind HFT books rarely see coming and MFT books can't ignore
Requirements
Requirements:
Strong grounding in statistical modelling, time-series analysis, and portfolio construction; comfort with the specific failure modes of lower-frequency strategies
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++ is a plus, not a requirement
Independent thinker, comfortable holding a position through drawdown without panicking or getting attached to it
Experience with crypto markets or other 24/7, fragmented liquidity environments is an advantage, not a prerequisite
Ability to work in a collaborative, high-performance environment where feedback is direct and iteration cycles are fast