Key Requirements / Qualifications: (essential unless otherwise stated)
• 3–5 years of relevant experience researching signals across commodity and cross-asset markets.
• Strong proficiency in R or Python, with the ability to work comfortably with large financial datasets.
• Solid grounding in statistical and mathematical modelling, with the judgment to choose the right tool for the problem at hand.
• Understanding of portfolio construction, optimization, and risk analysis.
• Comfort reading academic literature and translating it into testable ideas.
• Fluent use of AI tools in research and coding, combined with the discipline to verify outputs.
• Familiarity with transaction costs and their impact on signal design is a plus.
• Experience in systematic trading is a plus.
• Strong academic record with a degree in a quantitative discipline, such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Economics, from a leading university; a PhD or Master’s is advantageous.
• Intellectual curiosity and a genuine interest in markets and the forces that drive them, not only in methods.
• A hands-on, rigorous approach, with the motivation to follow an idea from intuition through testing to implementation.
• Excellent written and spoken English, with the presence and credibility to present work to institutional clients and defend it effectively.
• Highly organized, with the ability to manage multiple research threads in parallel.
• Collaborative and comfortable working closely with portfolio managers, researchers, and clients.