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Head of Quantitative Research & Structuring – Global Markets
Klay
Dubai, UAE
Full-time
Mid-Senior
Onsite
Discovered 2 weeks ago
Quantitative researchQuantitative strategy and structuringPortfolio constructionRisk managementMachine learningFeature engineering, model tuning, and validation
Role Overview
Lead a team of quantitative researchers and structurers, reporting to the Head of Global Markets and serving as a member of the Investment Team.
The role calls for at least 12 years of experience researching and developing quantitative trading portfolios.
Key Skills for This Role
Quantitative researchQuantitative strategy and structuringPortfolio constructionRisk managementMachine learningFeature engineering, model tuning, and validation
Full Job Posting
About the role
Lead a team of quantitative researchers and structurers, reporting to the Head of Global Markets and serving as a member of the Investment Team.
The role calls for at least 12 years of experience researching and developing quantitative trading portfolios.
Responsibilities
- Research, develop, and maintain quantitative methodologies for traditional single-stock style factor strategies, non-traditional thematic factor strategies, non-linear risk factor strategies, and portfolio construction frameworks.
- Contribute centrally to portfolio design, construction, and risk management to meet return and risk objectives, including model portfolio development.
- Source quantitative content from the sell-side and select strategies that suit investment objectives; refine strategies with sell-side partners as appropriate.
- Apply machine learning to generate predictive insights, including feature engineering, model tuning, and validation for robustness and performance.
- Analyze large, multi-source financial datasets to identify trends and risk drivers.
- Support trading and investment teams with data-driven insights and analytical tools.
- Collaborate across functions to translate business requirements into scalable technical solutions.
- Test and monitor models to ensure accuracy and ongoing performance.
Qualifications
- Master’s degree in Financial Engineering, Mathematical Finance, Data Science, Statistics, or a related quantitative discipline.
- At least 12 years of professional finance experience in quantitative research, strategy, or structuring.
- Experience in asset management, banking, or investment firms is preferred.
- Strong proficiency in Python, including Pandas, NumPy, and Scikit-learn; TensorFlow or PyTorch experience is a plus.
- Experience with unstructured datasets is a plus; most work is expected to involve structured datasets.
- Solid understanding of the pros and cons of various machine learning techniques.
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