About the Firm:
Our client is a high-performing quantitative trading firm known for its disciplined research culture and consistent alpha generation across global markets. As part of their strategic expansion, they are seeking a Director-level Quantitative Trader to drive strategy development, portfolio ownership, and the build-out of a world-class systematic trading team.
Key Responsibilities
- Strategy Research & Alpha Development - Lead the end-to-end development of systematic midlow frequency strategies by researching predictive signals, market structure, and regime behaviours using statistical and machine learning methods, and ensuring all models meet rigorous robustness, performance, and risk standards before deployment.
- Portfolio Management & Risk Oversight - Manage live portfolios across execution, risk controls, position sizing, turnover, and performance diagnostics, while collaborating with execution teams to optimise execution models and continuously evaluating and adjusting strategy behaviour to mitigate drawdowns as market conditions evolve.
- Team Build-Out & Leadership - Play a central role in building and scaling a high-performance trading and research team by hiring, training, and mentoring talent, establishing best practices across research and model deployment, and fostering a culture of intellectual curiosity, collaboration, and scientific rigor.
- Technology, Data & Infrastructure Collaboration - Work closely with data and software engineering teams to optimise datasets, enhance simulation frameworks and research tooling, improve production reliability, and drive automation and workflow efficiency across research and trading operations.
- Performance Reporting & Stakeholder Communication - Deliver clear strategy updates, performance reviews, risk analytics, and trading insights to senior leadership while leading post-trade analysis and contributing to firm-wide improvements in trading infrastructure and research methodology.
Qualifications
Education
- Bachelor's or Master's degree in Mathematics, Statistics, Computer Science, Engineering, Finance, or other quantitative fields.
- Advanced qualifications (PhD, CFA, FRM) are beneficial but not mandatory.
Experience
- 812+ years in quantitative trading, systematic strategy development, or portfolio management within a hedge fund, proprietary trading shop, or investment bank.
- Demonstrated success deploying profitable midlow frequency strategies in live environments.
- Experience hiring, mentoring, or developing quantitative talent is strongly preferred.
Technical & Market Expertise
- Strong Python proficiency with the ability to design robust backtests, simulations, stress tests, and scenario analysis. Deep understanding of market data structures (tick/LOB, fundamentals, alt-data), large-scale dataset handling (SQL/columnar/time-series DBs), and research pipelines.
- Solid knowledge of market microstructure across crypto and traditional markets, including FIX and websocket/REST connectivity. Skilled in execution optimisation: slippage modelling, order-type behaviour, venue selection, queue dynamics, and transaction cost analysis.
- Familiarity with distributed systems, latency considerations, and fault-tolerant trading environments. Comfortable partnering with engineers on performance bottlenecks, data validation, observability/monitoring, deployment workflows, and version control.
Leadership & Soft Skills
- Strong leadership presence with the ability to mentor, motivate, and upskill researchers, combined with a high-ownership mindset and a disciplined, scientific approach to trading decisions. Possesses excellent communication skills to articulate research findings and portfolio updates clearly to both technical and non-technical stakeholders.
Application Process
Interested candidates should submit their resume to Tina Wang at [Confidential Information], quoting the job title and reference number. Only shortlisted candidates will be contacted.
License No: 24S2395
Registration No: R2090553
