Join a high-impact team responsible for advancing portfolio construction capabilities and investment decision frameworks. In this role, you will apply quantitative expertise to develop innovative models, optimization techniques, and analytical solutions that support portfolio design, risk management, and asset allocation across the Global Private Bank.
As a Quantitative Associate within the Managed Investments team, you will help shape the next generation of portfolio construction capabilities, partnering closely with investment teams, portfolio managers, product specialists, and technology teams
You will contribute to the development of portfolio construction methodologies, risk-based sizing frameworks, asset allocation models, and advisor-facing analytical tools that enhance investment outcomes and create a more scalable and consistent investment process.
You will require comfort leveraging artificial intelligence and machine learning technologies to enhance investment research and portfolio construction workflows. You will identify opportunities to apply intelligent automation tools across the investment process while maintaining appropriate transparency and risk controls.
You will get the opportunity to influence both current portfolio construction practices and the future evolution of the firm's portfolio design platform through data-driven research, model innovation, and disciplined governance.
Job Responsibilities:
- Design, develop, and enhance quantitative models and portfolio construction frameworks used across asset allocation, portfolio optimization, and investment solution design.
- Conduct research on asset allocation methodologies, risk budgeting techniques, portfolio diversification approaches, and investment optimization frameworks to improve client outcomes.
- Develop and maintain analytical tools that support portfolio construction decisions, including risk-based sizing, scenario analysis, stress testing, tracking error analysis, and portfolio diagnostics.
- Evaluate and propose enhancements to existing portfolio construction methodologies through empirical research, back-testing, and performance attribution analysis.
- Partner with investment teams, product specialists, and technology stakeholders to implement portfolio construction capabilities and integrate quantitative research into advisor workflows and investment platforms.
- Support governance processes by documenting methodologies, preparing research materials, monitoring model performance, and ensuring analytical frameworks remain robust and transparent.
- Analyze large investment and market datasets to identify opportunities for improving portfolio construction processes, investment recommendations, and client portfolio outcomes.
- Manage multiple initiatives simultaneously in a dynamic environment while maintaining strong analytical rigor, execution discipline, and attention to detail.
Required qualifications, capabilities, and skills:
- 6+ years of experience in quantitative research, portfolio construction, asset allocation, risk analytics, or a comparable investment-focused analytical role.
- A strong foundation, gained through formal education or rigorous self-study, in a quantitative discipline such as mathematics, statistics, engineering, computer science, or a related field.
- Strong understanding of portfolio theory, asset allocation, investment risk management, and capital markets across equities, fixed income, and alternative investments.
- Experience developing quantitative models, optimization frameworks, statistical analyses, and investment decision-support tools.
- Proficiency in Excel, Python, Git, SQL, and data analysis libraries (e.g., pandas, NumPy, scikit-learn), with the ability to rapidly learn and apply new technologies and analytical platforms.
- Experience working with large financial datasets and conducting research involving market data, portfolio holdings, performance, and risk measures.
- Demonstrated ability to bridge quantitative research and practical portfolio implementation, translating analytical insights into actionable investment decisions.
- Strong communication skills with the ability to explain complex quantitative concepts to both technical and non-technical stakeholders.
Preferred qualifications, capabilities, and skills:
- CFA, FRM, or progress toward completion.
- Experience with portfolio optimization techniques, factor models, multi-asset allocation frameworks, and investment risk systems.
- Comfort applying AI, machine learning, and intelligent agent technologies to investment workflows, with the ability to identify practical use cases that enhance research, portfolio construction, and investment decision-making.
- Familiarity with advisor-facing investment platforms, portfolio construction tools, and scalable investment solutions.
- Knowledge of performance attribution, tracking error analysis, risk decomposition, and scenario-based portfolio analytics.
- Ability to adapt quickly to evolving business priorities, emerging technologies, and new investment research methodologies.