Quantitative Trader (P&L Owner | Crypto)

**About the role** You will run your own systematic trading book end-to-end — from signal research and strategy design through backtesting, live deployment, execution and risk management. This is a high-autonomy, P&L-owning seat for a self-sufficient trader who can independently build, run and improve profitable mid-to-low frequency strategies in crypto market. **Key responsibilities** - Independently own and trade a dedicated account, taking full responsibility for strategy P&L and risk - Research, develop and deploy mid-to-low frequency systematic strategies — market-neutral, CTA / trend-following, statistical arbitrage, multi-factor equity, funding-rate and cross-exchange arbitrage — across crypto (spot, perpetuals, derivatives) and US equities - Manage the full trading lifecycle: data pipelines, factor research, backtesting, parameter optimisation, live execution, and real-time risk and inventory monitoring - Continuously improve strategy capacity, Sharpe and drawdown control as market conditions evolve - Maintain rigorous risk discipline and operate within firm-wide risk limits **About you** - 3+ years of mid-to-low frequency systematic / quantitative trading experience, gained at a top-tier quantitative trading firm — a leading quant hedge fund or proprietary trading firm - A demonstrable, attributable live track record running your own strategy, with clear metrics (returns, Sharpe, maximum drawdown, capacity) - Hands-on expertise in market-neutral and/or CTA / systematic strategies, ideally in crypto and/or US equity markets; experience with statistical arbitrage or multi-factor models is highly valued - Strong programming skills in Python (and/or C++) covering the full pipeline: research, backtesting, execution and monitoring - Solid foundation in mathematics, statistics, probability and/or machine learning - Proven ability to work independently, and self-manage with strong risk awareness - Preferred: Live trading track record in crypto / digital-asset markets (CEX and/or DEX) and/or US equities - Preferred: Experience with multi-factor models, alternative data, NLP / sentiment signals, or machine-learning-driven research - Preferred: Advanced degree (MSc / PhD) in a quantitative discipline — mathematics, statistics, physics, computer science, financial engineering or similar