- Work with the Head of ARU to develop the strategic vision and research pipeline for execution research across equities and listed asset classes.
- Influence execution outcomes by delivering innovative quantitative and systematic solutions in a collegiate and collaborative environment. Contribute to team research discussions and provide mentorship to junior colleagues.
- Work on areas such as counterparty selection, algo and venue selection, market impact modelling, intraday trade scheduling, and execution strategy. Systematically identify drivers of execution performance and develop frameworks for their analysis.
- Proactively link themes, concepts, and ideas across asset classes to deliver insightful market analysis with a liquidity and microstructure perspective.
- Manage projects from initial idea through to production, working closely with traders to incorporate their insights and intuition into your work. Leverage a dedicated team of developers to implement models and quickly see your impact.
- Demonstrate intellectual flexibility and curiosity about markets, identifying opportunities to enhance GIC's approach to execution and understanding of market microstructure.
- Build a strong understanding of internal mandates and investment styles to identify potential projects. Regularly interact with and present to internal risk takers, tailoring content to various audiences.
- Have access to large transaction and market datasets through our in-house multi-asset research platform and connect with domain experts across buy and sell-side to deepen your understanding of market structure and topical themes.
Qualifications and Skills
The ideal candidate will possess:
- 8 to 10 years of professional experience in a quantitative role (e.g., analyst, strategist, researcher, trader, data scientist, quant product manager).
- A proven track record of producing models, analysis, reports, and tools based on quantitative methods, ideally in a client-facing capacity.
- A strong interest in global equity market microstructure and current events, with the ability to transform data into actionable insights.
- An in-depth understanding of electronic and algorithmic execution and related analyses such as Transaction Cost Analysis (TCA) and expected cost models.
- Experience working directly with traders (both low-touch and high-touch) and developers is preferred but not essential.
- A solid understanding of the relevance and application of machine learning methods to execution and counterparty selection.
- Direct experience in planning research projects and managing multiple stakeholders.
- Excellent coding skills in languages such as Python, R, SQL, and kdb/Q.
- Exceptional attention to detail and a commitment to maintaining the highest standards of accuracy and rigour in all tasks.
