Head of Quant Trading (Relocate to Dubai, UAE)

Overview

As the Head of Quant Trading, you will lead the development, optimization, and deployment of state-of-the-art algorithmic trading strategies and quantitative models. This role demands deep technical expertise in data science, machine learning, advanced statistical methods, and software engineering, combined with a strong understanding of financial markets and trading dynamics.

Key Responsibilities

• Quantitative Strategy Development & Research:
• Algorithm Design: Lead the design, development, and refinement of proprietary trading algorithms using advanced statistical and machine learning techniques.
• Modeling & Simulation: Develop quantitative models for forecasting, signal generation, and risk management. Oversee rigorous backtesting and simulation processes to validate models against historical data.
• Data Analysis: Utilize big data analytics and advanced statistical methods to extract actionable insights from large, diverse datasets (e.g., market microstructure, alternative data sources).
• Innovation: Stay at the forefront of quantitative finance research and adopt emerging techniques (e.g., deep learning, reinforcement learning) to enhance trading strategies.
• Technical Infrastructure & Implementation:
• System Architecture: Collaborate with IT and engineering teams to design and optimize high-frequency, low-latency trading systems. Ensure robust, scalable infrastructure for real-time data processing and trade execution.
• Software Development: Oversee the development and maintenance of trading systems and tools. Utilize programming languages such as Python, C , Java, or MATLAB to implement trading algorithms and performance monitoring systems.
• Automation & Integration: Implement automated pipelines for data ingestion, processing, model training, and strategy deployment. Ensure seamless integration with execution platforms and market data feeds.
• Technology Stack Management: Evaluate, select, and integrate advanced analytics platforms, databases, and cloud solutions to support research and trading activities.
• Performance Analysis & Risk Management:
• Metrics & Analytics: Develop and maintain robust performance metrics to assess algorithm efficiency, trade execution quality, and risk-adjusted returns. Use real-time analytics to monitor strategy performance and market conditions.
• Risk Controls: Collaborate with risk management teams to integrate sophisticated risk models and dynamic hedging strategies. Ensure that all trading algorithms adhere to predefined risk limits and compliance standards.
• Optimization: Continuously refine and optimize models based on performance analytics, market feedback, and evolving conditions. Conduct sensitivity analysis and scenario testing to anticipate and mitigate potential risks.
• Collaboration & Technical Leadership:
• Team Mentorship: Lead and mentor a multidisciplinary team of quantitative researchers, data scientists, and software developers. Provide technical guidance and foster a culture of innovation and rigorous analysis.
• Cross-Functional Integration: Work closely with other departments (e.g., risk, IT, operations) to ensure alignment of technical strategies with broader business objectives.
• Documentation & Code Quality: Ensure high standards in code quality, documentation, and software engineering practices across the quant team. Promote best practices in model development and deployment.

Qualifications & Experience

• Educational Background:
• Bachelor's or Master’s degree in Quantitative Finance, Mathematics, Statistics, Computer Science, Engineering, or a related technical discipline.
• Professional Experience:
• Extensive experience (typically 8 years) in quantitative trading, algorithmic trading, or a similar technical role within financial institutions, hedge funds, or proprietary trading firms.
• Proven track record of developing and deploying successful algorithmic trading systems.
• Technical Expertise:
• Programming: Advanced proficiency in one or more programming languages (e.g., Python, C , Java, MATLAB). Experience with software development methodologies and version control systems.
• Data Science & Machine Learning: Expertise in statistical modeling, data mining, and machine learning techniques. Familiarity with libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, or similar.
• Systems & Infrastructure: In-depth knowledge of high-performance computing, real-time data processing, and low-latency system design. Experience with cloud-based architectures and distributed computing is a plus.
• Financial Markets: Solid understanding of financial instruments, market microstructure, and the dynamics of electronic trading.
• Analytical & Problem-Solving Skills:
• Ability to translate complex market data and research insights into actionable trading strategies.
• Strong quantitative and analytical skills, with a keen eye for detail in model validation and performance optimization.