At HSBC, the health and well-being of our employees remains of utmost importance. Many of our roles are permitted to work from home (in states in which HSBC is licensed to operate) until further notice. Upon resumption of normal operations, this role may be performed at our New York, New York office.

Our Assistant Vice President (AVP), Quant Modeling – Stress Testing will be responsible for designing, developing and maintaining pre-provision net revenue (PPNR) models used in bank stress testing (CCAR). You will be responsible for establishing fit-for-purpose models, with strong governance and analytics

About Us

HSBC is one of the largest banking and financial services organizations in the world, with operations in 64 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people to fulfill their hopes and realize their ambitions.

On a typical day your activities could include the following:

Working with business partners to provide financial and technical analysis and recommendations regarding current and/or proposed PPNR models.
Working with businesses, risk and finance teams to submit and validate data and analyze the consolidated results.
Production of the final regulatory 14A submission and data quality assurance of the submission; and partnering with other CCAR teams such as documentation, process or review and challenge in order to provide and analyze results.
Implementing/onboarding models developed onto in house developed model execution platform.
Model development, validation and model execution platform code maintenance and enhancement.

Adhere to the governance standards established for scenario design, including, but not limited to the review and approval of key decision items by the U.S. CFO, U.S. CRO, Head of Strategic Planning and Stress Testing, and U.S. head of Central Scenarios and Modeling
Ensure that the models are developed as per established framework.
Help identify drivers related to individual businesses, and incorporate them in proposed models.