What you will be doing
Develop and improve AI-driven quantitative investment strategies in financial markets within the dedicated China research team. Support all strategies from alpha generation through to trade execution and implementation, working closely with other team members to design, build, and enhance strategies using cutting-edge machine learning and AI techniques.
Core responsibilities include:
- Alpha Generation & Idea Discovery: Leverage large language models (LLMs), NLP, and alternative data pipelines to identify novel investment signals and innovative data sources
- Data Gathering & Refinement: Apply AI-powered data processing and feature engineering techniques to gather, clean, and structure complex datasets for modeling at scale.
- Modeling & Statistical Analysis: Design and implement deep learning, reinforcement learning, and statistical ML models to build, backtest, and refine various quantitative models.
- Interpretation & Presentation: Translate complex AI model outputs into actionable investment insights, ensuring model interpretability and explainability when communicating results to stakeholders.
- Implementation Research: Conduct research on AI-enhanced implementation aspects of investment strategies, including ML-based trading cost models, learned risk models, AI-assisted portfolio optimization, and dynamic portfolio construction.
Key competencies
- Advanced degree in Computer Science, Statistics, Mathematics, Finance/Economics or related quantitative field from a top-tier institution
- Passion in investment research with strong intuition and the ability to think-out-of-the-box
- Background in core ML theory: optimization, probabilistic modeling, deep learning architectures (transformers, diffusion models, etc.)
- Strong publication record or thesis work in ML/AI (conference papers at NeurIPS, ICML, ICLR, ACL etc. are preferred); hands-on experience in fine-tuning large-scale foundation models
- Experience with cloud environments and multi-machine CPU/GPU setups
- Ability to communicate complex ideas clearly, strong collaboration skills to partner with other teams to implement ideas into products
- Prior experience in the investment field is a plus but not required
