Portfolio Manager – Intraday, AI-Driven Strategies (Equities/Futures, Europe Focus)

This range is provided by Fortis Recruitment. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

The Firm

A leading quant hedge fund known for its cutting-edge technology, machine learning expertise, and data-driven investment strategies. They specialise in systematic trading across asset classes, leveraging AI, deep learning, and statistical arbitrage models to generate sustainable alpha.

The firm operates in a highly competitive, low-latency trading environment, requiring Portfolio Managers to deploy innovative, scalable, and robust systematic strategies with strict risk controls. It provides access to world-class infrastructure, proprietary datasets, and an advanced research environment, enabling its teams to develop and optimize high-frequency and intraday trading strategies.

The Opportunity

• Design, backtest and implement intraday systematic trading strategies using AI, machine learning, and deep learning models.
• Develop predictive models for price movements, order flow, volatility forecasting, and market microstructure signals.
• Ensure strategies remain orthogonal to existing investment portfolios within the firm.
• Incorporate alternative data sources and innovative techniques to enhance alpha generation.
• Implement robust execution algorithms to optimize market impact and slippage.
• Adapt to changing market conditions through dynamic model retraining and reinforcement learning techniques.
• Work within a state-of-the-art, cloud-based research and trading infrastructure.
• Leverage high-performance computing for large-scale simulations and model training.
• Utilize advanced Python, C++, and TensorFlow/PyTorch frameworks for AI-driven trading research.

Skills and Qualifications:

• PhD in Computer Science, Applied Mathematics, Machine Learning, or a related quantitative field from a top global university (e.g., MIT, Stanford, Oxford, Cambridge, ETH Zurich, ENS, Tsinghua, etc.).
• Annual PnL record of $20m over at least three years and Sharpe Ratio of 2.
• Deep expertise in AI-driven trading models, including deep learning, reinforcement learning, and non-linear statistical methods for financial markets.
• Experience trading European equity or futures markets, with a high Sharpe Ratio and strong alpha capture in short-term signals.
• Strong programming skills (Python, C++, TensorFlow, PyTorch, SQL) and ability to build scalable research and trading pipelines.
• Deep understanding of market microstructure, execution algorithms, and transaction cost analysis in electronic trading environments.
• Ability to deploy models in a high-performance, low-latency trading environment.

The Offer:

• Work with one of the most sophisticated data-driven trading environments, leveraging proprietary datasets and AI tools.
• The freedom to develop innovative strategies while leveraging cutting-edge infrastructure and risk management support.
• Industry-leading P&L-based compensation structure aligned with performance and risk-adjusted returns.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Finance

Industries

Investment Management

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