The role combines quantitative research with applied multi-asset portfolio management, translating quantitative models and signals into portfolio decisions, implementation, and clear communication. 1. Manage Quantitative Multi-Asset Investment Strategies - Partner with the quantitative team on portfolio optimisation, model improvements, and implementation, maintaining clear documentation of methodologies and investment implications. - Assist in defining portfolio objectives, risk budgets, and constraints; interpret and challenge optimisation outputs and translate them into positioning consistent with the investment process. - Manage standard and customised multi-asset portfolios using the Bank's quantitative framework, applying cross-asset investment judgement. - Apply cross-asset knowledge to portfolio construction, asset allocation, and risk management, including equity and fixed-income applications. Assess performance, exposures, and the investment implications of model outputs. - Support ongoing development of multi-asset strategies, using the Bank's quantitative framework as well as custom risk and alpha overlays. 2. Develop Quantitative Portfolio Applications and Tools - Work with the quantitative team on derivatives overlays, hedging, and other systematic investment applications. - Collaborate with the AI team to interpret quantitative signals and portfolio changes, using market and Investment Committee context to develop and validate investment analysis and explanations. - Oversee portfolio data quality and improve analytical tools and dashboards for performance analysis, risk monitoring, and implementation. - Share knowledge, support colleagues, and coach junior team members in the application of the investment philosophy and quantitative portfolio processes and tools. 3. Support Communication and Distribution Efforts - Explain portfolio decisions, models, and signals clearly, and prepare presentations and investment information packs for internal and external audiences. - Work with Client Portfolio Managers and distribution colleagues on investment communication, participating in client and prospect meetings as required. Qualifications & Experience: - More than five years of experience in applied portfolio management positions, with proven multi-asset or cross-asset experience. - Experience in systematic investing, quantitative trading, and cross-asset factor models for alpha generation or risk management; sound financial markets knowledge. - Excellent Python skills and strong knowledge of statistics, data science, finance, machine learning, and financial time-series analysis, with experience applying these to quantitative investment solutions. Experience with SQL, PostgreSQL, and MongoDB. - Research and technical-writing experience, with academic publications an advantage; rigorous attention to models, data, and outputs. - Excellent communication and presentation skills, including the ability to explain complex investment concepts clearly. Fluent professional English; proficiency in Mandarin, Cantonese, or Japanese is an advantage. - Self-motivated, hard-working, and collaborative, with a growth mindset, integrity, and commitment to regulatory and company requirements. - A master’s degree in quantitative finance or financial engineering is preferred.