Quantitative Trader – Equities (Strategy Monetization)

IMC is hiring a Quantitative Trader to focus on monetization research and back testing for high- to mid-frequency delta-one equity strategies. This role emphasizes research depth, systematic evaluation, and capital efficiency, partnering closely with quant researchers and engineers to turn signals into scalable, profitable trading strategies. Based in Sydney, this role is ideal for candidates who excel at research-driven trading problems, large-scale data analysis, and rigorous performance validation. For exceptional candidates from top global trading firms, Hong Kong location may be considered. Core Responsibilities Research and evaluate new trading signals and strategy ideas with a focus on monetization potential Design and run large-scale back tests to assess PnL, risk, capacity, and robustness Analyse transaction costs, market impact, and execution assumptions within back testing frameworks Optimize portfolio construction, capital allocation, and risk controls across strategies Work with engineers to improve back testing infrastructure, data quality, and research tooling Partner with live traders to ensure research assumptions align with real-world execution behaviour Drive strategies from research validation through production readiness Skills & Experience Degree in a quantitative field (Mathematics, Physics, Computer Science, Engineering, Economics, or similar) 3+ years of experience in quantitative trading or monetization research, preferably in equities Strong experience with back testing frameworks, large datasets, and systematic performance evaluation Deep understanding of market microstructure, transaction costs, and scalability constraints Strong programming skills (Python/C++ strongly preferred); ability to write clean, research-grade code Rigorous, detail-oriented mindset with strong statistical intuition Experience at leading systematic or proprietary trading firms is a strong plus About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.