Quantitative Researcher - Applied Research Unit, Portfolio Execution Group

Quantitative Researcher - Applied Research Unit, Portfolio Execution GroupLocation: Singapore (as preference), but could be based in London/New YorkJob Type: PermanentOverviewOur client is one of the world’s largest sovereign wealth funds. With over 2,000 employees across 11 locations around the world, they invest in more than 40 countries globally across asset classes and businesses. Working with them gives you exposure to an extraordinary network of the world’s industry leaders. Portfolio Execution GroupPortfolio Execution Group encompasses multiple teams that perform a range of functional roles including trade execution, funding & liquidity management, securities financing, and applied quantitative research.

This group comprises three sub-teams – Global Trading Unit (GTU), Balance Sheet Management Group (BMG), and Applied Research Unit (ARU). Applied Research Unit (ARU)The Applied Research Unit (ARU) specializes in multi-asset quantitative research, focusing on market microstructure and liquidity to improve execution outcomes and systematize decision-making processes. They collaborate closely with traders, investment teams, risk management, and total portfolio functions to enhance strategy implementation while providing valuable insights into liquidity and market structure.

Position OverviewThey are seeking a highly qualified candidate with extensive experience in equity markets to support the team’s growth and enhance their capacity to deliver proactive analysis and data-driven consultancy to internal stakeholders. While this role is based in Singapore, the successful candidate will play a crucial role in contributing to the team's initiatives across global markets. Key ResponsibilitiesAs a Quant Researcher within ARU, you will: 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 company'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 SkillsThe ideal candidate will possess: Strong 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.