Quantitative Researcher – Absolute Return (Digital Assets)

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:

1. Designing and validating systematic signals grounded in economic or behavioural rationale
2. Rigorous time-series research with explicit regime awareness
3. Portfolio construction and capital allocation within an absolute-return framework
4. Building robust, production-grade research code and infrastructure
5. 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

1. Experience researching or trading systematic strategies targeting positive P&L independent of market direction
2. Clear understanding of risk-adjusted performance metrics (Sharpe, Sortino, drawdown control, tail exposure)
3. Evidence of taking signals from research to live capital allocation
4. Appreciation for portfolio interaction effects and capital efficiency

Quantitative Depth

1. Strong statistical foundations (inference, regression, hypothesis testing, time-series modelling)
2. Sound judgement around machine learning — when it adds value and when it does not
3. High standards around data integrity, leakage prevention, and experimental design
4. Ability to distinguish structural edge from noise

Engineering Maturity

1. Advanced Python in a research production environment
2. Writes clean, testable, version-controlled code
3. Comfortable operating in shared research infrastructure

Background

1. 3–8 years in systematic buy-side research, quant hedge funds, or equivalent alpha-focused environments
2. 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
3. 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