Head of Portfolio Construction & Risk

To lead the development and integration of portfolio construction and risk frameworks across the firm’s investment offerings. This role is responsible for embedding risk methodologies into a range of strategies, including bottom-up active, quantitative, and outcome-based approaches. The Head of Portfolio Construction & Risk will also guide the firm's adoption of machine learning and quantitative tools, support the development and backtesting of new strategies, and provide risk oversight across all portfolios and be part of the Investment Committee. As the firm undergoes rapid growth and aims to position itself as a regional leader in the GCC and beyond, this role will be central in ensuring portfolios are constructed and monitored with a disciplined and scalable risk approach and supports innovation of new products and capabilities in a rapidly changing asset management environment.

• Design and implement comprehensive portfolio risk frameworks across active, quantitative, passive, and outcome-based strategies.
• Guide the firm’s approach to risk model selection and validation, drawing on familiarity with tools such as Barra, Axioma, Bloomberg, FactSet etc.
• Support the product development process by contributing portfolio construction insight, including backtesting of strategies and alignment with investment objectives.
• Lead the development and integration of machine learning and AI tools to support portfolio design and risk assessment.
• Create and maintain robust portfolio risk reporting, monitoring, and escalation protocols.
• Develop quasi-active, factor-based strategies with defined risk budgets and tracking error targets.
• Construct customised portfolios for a range of client and product types, including institutional mandates and mutual funds.

• Minimum 10 years’ experience in investment risk, quantitative research, or portfolio construction within asset management.
• Solid quantitative background with expertise in risk modelling, portfolio optimisation, and performance analysis.
• Familiarity with major risk systems and tools such as Barra, Axioma, Bloomberg PORT, and FactSet.
• Familiarity with equity and fixed income asset classes as well as mmulti asset portfolios
• Strong understanding of active, passive, quantitative, and outcome-based portfolio management techniques.
• Proven experience in integrating machine learning or algorithmic methods within portfolio design or risk functions.
• Skilled in backtesting, scenario analysis, and developing portfolio analytics aligned to investment objectives.
• Demonstrated ability to build client- and product-oriented portfolio solutions.
• Excellent analytical, communication, and cross-functional collaboration skills.
• Finance / quantitative-related Bachelor's or Master’s degree , with CFA or equivalent professional qualifications preferred