Portfolio Manager

6 days ago

Mumbai, India AAA Global Full time

Job Description: Portfolio Manager – MFT / HFT Strategies Location: Open in India/Globally Department: Quantitative Trading / Portfolio Management Employment Type: Full-Time Reports To: Portfolio Manager/Chief Investment Officer / Head of Quantitative Strategies Role Overview : We are seeking an experienced Portfolio Manager (PM) to develop, manage, and scale medium-frequency and high-frequency trading strategies across global markets. The ideal candidate possesses a strong quantitative background, proven alpha-generation capabilities, and hands-on experience deploying systematic strategies in low-latency environments. You will be responsible for the full lifecycle of strategy development—from ideation and research to production deployment and performance management—while working closely with quantitative researchers, data engineers, and trading infrastructure teams. Key Responsibilities Strategy Research & Development Develop, test, and optimize systematic MFT/HFT trading strategies using advanced statistical, machine learning, and microstructure-aware techniques. Conduct extensive alpha research, feature engineering, and signal validation using large, high-frequency datasets. Evaluate strategies for robustness, stability, and sensitivity via simulation and backtesting frameworks. Portfolio & Risk Management Manage daily trading performance—including PnL attribution, drawdown analysis, and factor decomposition. Optimize capital allocation, turnover, and execution to maximize Sharpe ratio and minimize slippage/latency-related losses. Monitor risk exposures (market, liquidity, execution, model drift) within defined limits. Execution & Infrastructure Collaboration Work with low-latency engineers to integrate strategies into production trading systems. Collaborate with execution teams to refine order routing, market-making, and microstructure-driven execution tactics. Continuously benchmark and improve execution efficiency (fill rates, market impact, latency). Data & Model Governance Work closely with data engineering teams to acquire, clean, and structure tick-level and alternative datasets. Maintain high standards of model documentation, reproducibility, and compliance. Discuss with @palak@aaaglobal.co.uk

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