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A Quantitative Trader (Quant Trader) leverages mathematical models, statistical analysis, and computer algorithms to identify and exploit market inefficiencies for profit. Operating at the intersection of data science, finance, and software engineering, a Quant Trader is responsible for the end-to-end execution, risk management, and overall Profit & Loss (P&L) of systematic trading strategies across global financial markets.

Strategy Implementation & Execution: Deploy and monitor automated algorithmic strategies in live markets, ensuring precise execution and minimal market impact.

Live Risk Management: Monitor real-time system performance, adjust strategy parameters based on intra-day macro events, and aggressively manage exposure limits, delta risks, and capital drawdown.

Data Analysis & Backtesting: Clean, process, and evaluate historical market datasets using statistical software to test new signals and validate strategy mechanics.

Cross-Functional Collaboration: Partner with Quant Researchers to implement new mathematical models and Quant Developers to optimize high-frequency execution infrastructure.