Snr Quant Researcher, Systematic Investment Strategies & Data (Dir), UAE

This large Asset Manager, based in the Emirates, has a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.  They now seek a Snr Quant Researcher, to play a pivotal role in their peer review and testing team. Leveraging your expertise in systematic investing, signal construction, long/short portfolio management, machine learning, financial econometrics, or derivatives pricing, you will rigorously test strategies and researcher’s hypotheses.  You’ll excel in crafting compelling narratives from experiments, conveying the insights derived from your research to both technical and non-technical stakeholders.

KEY RESPONSIBILITIES:

• Collaborate closely with data curation specialists, feature analysts, & strategy developers to validate investment strategies & algorithm toolkits.
• Design and execute experiments to confirm causal connections in investment strategies utilising alternative data and highly innovative approaches
  
• Uncover latent relationships within complex datasets, drawing on your proficiency in quant methodologies.
• Develop robust theoretical frameworks that underpin those strategies, aligning with market dynamics and trends.
• Rigorously test hypotheses and refine theories based on empirical evidence and analysis outcomes.
• Transform research findings into compelling data narratives, communicating insights to both technical and non-technical stakeholders.

KEY SKILLS & EXPERIENCE:

• 5-20 years’ experience in quant research, gained at a large Asset Manager or a hedge fund running systematic strategies (but not UHF) utilising alternative data and highly innovative approaches
• Knowledge of financial markets, trading strategies, and investment theories.
• Published research papers or contributions to relevant research communities.
• Strong expertise in advanced statistical techniques, experimental design, quant methodologies.
• Strong Python
• Master's or PhD in a quantitative discipline (e.g. Maths, Stats, Physics, Econometrics, Machine Learning, or similar).
• Also could be interested in CTA experience where you are strong in the risk premia, to which advanced mathematical techniques are applied throughout the process