Full job description We’re partnering with a research-led quantitative hedge fund deploying systematic absolute-return strategies in digital asset markets. The focus is medium-frequency, signal-driven research with disciplined portfolio construction and institutional-grade risk management.
This is not a latency, market-making, or benchmark-aware environment. Performance is defined by robust, risk-adjusted alpha generation across market regimes .
The Opportunity
You will operate as a true alpha researcher — owning ideas from hypothesis through to production — within a collaborative, high-conviction research team.
Scope includes:
*Designing and validating systematic signals grounded in economic or behavioural rationale
*Rigorous time-series research with explicit regime awareness
*Portfolio construction and capital allocation within an absolute-return framework
*Building robust, production-grade research code and infrastructure
*Contributing to risk controls that prioritise drawdown management and capital efficiency
Researchers are expected to consider edge durability, capacity constraints, and cross-regime robustness, rather than focusing on backtest optics.
Profile Sought
Absolute-Return DNA
*Experience researching or trading systematic strategies targeting positive P&L independent of market direction
*Clear understanding of risk-adjusted performance metrics (Sharpe, Sortino, drawdown control, tail exposure)
*Evidence of taking signals from research to live capital allocation
*Appreciation for portfolio interaction effects and capital efficiency
Quantitative Depth
*Strong statistical foundations (inference, regression, hypothesis testing, time-series modelling)
*Sound judgement around machine learning — when it adds value and when it does not
*High standards around data integrity, leakage prevention, and experimental design
*Ability to distinguish structural edge from noise
Engineering Maturity
*Advanced Python in a research production environment
*Writes clean, testable, version-controlled code
*Comfortable operating in shared research infrastructure
Background
*3–8 years in systematic buy-side research, quant hedge funds, or equivalent alpha-focused environments
*Candidates from discretionary macro, long-only, pure HFT/market-making, or crypto-only backgrounds without systematic alpha research experience are unlikely to be a fit
*Advanced degree (MSc/PhD) in a quantitative discipline strongly preferred
This is a role for researchers who think in terms of risk capital, robustness, and long-term edge persistence — not model complexity for its own sake