Quantitative Research Associate - Investment Solutions

Join a high-impact team shaping the future of lending solutions for HNI clients and the corresponding risk management. Leverage your quantitative expertise to develop innovative models and analytical frameworks to determine collateral requirements. Be part of a collaborative environment where your insights directly influence lending decisions withing the Private Bank.

As a Quantitative Research Associate within the Investment Solutions Quant Research and Model Review team, you will develop and enhance analytical tools to estimate Loan to Value (LTV) for capital market securities. You will collaborate with global partners to implement model improvements and ensure robust governance and performance monitoring. Your work will drive data-driven decision-making and support the evolution of next-generation LTV models.

Job Responsibilities:

• Collaborate with a team of quantitative researchers to develop analytical tools to estimate collateral requirement and the loan to value for tradable securities as well as analytics and tools that are relevant to other Business functions.

• Propose model enhancements and demonstrates its conceptual soundness via rigorous back-testing.

• Partner with Technology to design and implement cost-effective model changes and conduct implementation testing.

• Monitor model performance on a routine basis. Design and perform continuous risk monitoring.

• Conduct ad-hoc quantitative research and analysis.

• Be the point of contact for questions from Lending Business and Risk.

• Manage multiple priorities in a dynamic professional environment.

Required qualifications, capabilities, and skills

• Demonstrate previous experience in Loan to value estimation or portfolio risk analytics and asset management.

• Apply strong quantitative modeling and time series analysis skills.

• Exhibit knowledge of equity, fixed income, and alternative investment products.

• Hold a graduate degree in a quantitative discipline such as Math, Statistics, Finance, Economics, or Engineering.

• Utilize programming skills in Python and SQL, with a willingness to learn new tools.

• Manage financial data handling, retrieval, and modeling tasks effectively.

• Communicate complex concepts clearly in both written and verbal formats.

Preferred qualifications, capabilities, and skills:

• Attain CFA or FRM certification at any level.

• Demonstrate the understanding of lending business (collateral requirement, loan to value estimation, initial and maintenance margins, shortfall monitoring etc. for tradable securities).

• Adapt quickly to new analytical tools and technologies.