We are working with a $10bn Multi-Strategy Head Fund looking for a Quantitative Researcher with deep, hands-on expertise in LLMs and AI agents to apply cutting-edge machine learning methods to alpha research and portfolio construction. The ideal candidate is passionate about exploring how emerging AI technologies can enhance systematic investment strategies (equities, futures & options) and research automation within a multi-manager environment.
Key Responsibilities
• Research, prototype, and validate systematic trading signals across HK or US equity/future/option markets using advanced AI/ML methods.
• Design and implement rigorous backtesting with walk-forward validation, and robust statistical tests.
• Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods.
• Develop portfolio construction and optimization techniques and analysis tools to be able to enhance performance and track effects on portfolio execution.
• Collaborate with developers to transition research into production-ready strategies.
Requirements
• Masters or PhD in either Statistics, Math or Computer Science.
• Strong background in machine learning and statistical modelling (tree-based models, regularization, time-series ML).
• Proven hands-on experience with LLMs (e.g., fine-tuning, retrieval-augmented generation, agentic workflows, or model evaluation).
• Proficiency in Python (pandas, NumPy, scikit-learn, XGboost, PyTorch/TensorFlow).
• Understanding of time-series forecasting, cross-validation techniques, and avoiding look-ahead bias.
