Quantitative Researcher - Strategy

About the Role

The Abu Dhabi Investment Council (ADIC) is looking to recruit a Quantitative Researcher within its Strategy team. This position is critical in assisting the investment process by performing advanced quantitative research, developing models, and deploying AI-driven methodologies.

The role centers around supporting investment decisions across various public and private markets by creating and improving systematic signals, valuation models, and tools for portfolio construction. Collaboration with investment professionals will be essential to boost quantitative capabilities and create innovative investment approaches.

Key Responsibilities

• Develop and validate alpha signals and factor models across different asset classes leveraging statistical and machine learning methods.
• Execute quantitative research and build valuation models applicable to both public and private market investments.
• Design, backtest, and analyze quantitative frameworks, including systematic strategies and portfolio construction techniques.
• Create and refine risk management models, performance attribution systems, and investment analytics tools.
• Develop comprehensive quantitative applications supporting investment processes from data acquisition to deployment.
• Collaborate closely with the Strategy team investment professionals to provide research findings, model designs, and quantitative insights.
• Lead initiatives related to AI and machine learning to improve research methodologies and the investment workflow.

Requirements

• At least five years of experience in quantitative research, systematic investing, portfolio construction, asset allocation, or investment strategy roles.
• Solid background in quantitative research within public markets; knowledge of private markets is a valuable plus.
• Demonstrated experience in designing and implementing quantitative investment models or systematic strategies with thorough backtesting.
• Hands-on experience deploying AI and machine learning approaches to financial data and developing reliable analytical tools suitable for production environments.
• Bachelor's degree in quantitative fields such as Finance, Mathematics, Engineering, Computer Science, Statistics, Physics, or related disciplines.
• Advanced degrees (Master's or PhD) are highly regarded.
• Proficiency in Python or similar object-oriented programming languages with a track record of writing production-level code.
• Comprehensive knowledge of quantitative modeling concepts including time series analysis, factor modeling, and portfolio optimization techniques.
• Familiarity with machine learning libraries like scikit-learn, TensorFlow, or PyTorch.
• Experience with SQL databases, cloud computing platforms, and version control systems such as Git.
• Strong understanding of financial markets encompassing equities, fixed income, and private market instruments, and their roles in portfolio management and asset allocation.
• Excellent analytical aptitude and communication skills, capable of clearly presenting complex quantitative analysis to investment teams.