Quantitative Research Analyst (Systematic Trading Strategies)

Quant Lab SFO FZCO is a Dubai-based single family office trading proprietary family capital. The company combines quantitative research, AI-powered strategy development, and automated execution, built on disciplined risk control, strict position-sizing, and long-term performance. It is family-funded since 2021.

• Ability to make material decisions based on analysis and knowledge outcomes.
• Capacity to work effectively as the sole analyst and achieve high standards.
• Disposition to test assertions and exercise judgment without guidance.
• Quick effectiveness in unfamiliar domains.
• Intellectual honesty to report findings contradicting prior positions.
• Daily substantive use of AI coding and research tools such as Claude Code, Codex, or Copilot.
• Exceptional analytical ability to decompose ambiguous problems.
• Rigorous empirical judgment with appropriate skepticism towards unusually favorable results.
• Excellent written and spoken English; ability to communicate technical results to non-specialists.
• Sustaining and revising positions based on evidence.

Preferred:

• Three or more years in quantitative research, systematic trading, or data-intensive analytics, or demonstrable record developing and testing systematic strategies.
• Familiarity with backtest biases such as look-ahead bias, survivorship bias, in-sample parameter selection, and unmodelled transaction costs.
• Working knowledge of equity market mechanics and US equity markets.
• Ability to read and modify object-oriented code, e.g., C#.
• Degree in mathematics, statistics, physics, computer science, engineering, or quantitative finance.

• Develop new systematic strategies end to end, from initial hypothesis through data preparation, backtesting and validation to hand-off into live trading.
• Design and conduct backtests, and quantify the sources of divergence between simulated and live performance, including execution, liquidity and transaction-cost effects.
• Analyse trade-level data to establish where returns are generated and where they are lost.
• Quantify the expected impact of each finding, so that competing recommendations may be ranked on a common basis.
• Subject conclusions to out-of-sample testing, controls for overfitting and consideration of alternative explanations before presenting them.
• Implement strategy logic in the trading platform, directing AI coding assistants, and monitor deployed strategies for anomalies in execution and performance.
• Present findings, their quantified impact and the associated risks, together with a recommended course of action.

Candidates located elsewhere must be willing to relocate for no less than 50% of working time.