This VP role is part of the Quantitative Analytics (QA) Treasury team of a leading UK high impact bank. The team supports Treasury business in areas like Asset and Liability Management, Liquidity, Collateral and Hedge Accounting Management with the development and delivery of various quantitative models used for internal risk management and regulatory exercises.

Responsibilities:

The role focuses on Python based quantitative models that project balance sheet cash flows, liquidity risk and hedge accounting metrics under stress and resolution type scenarios and requires close collaboration with Treasury Finance, Risk and Technology partners to deliver robust, well controlled models in a regulated environment.

Requirements:

Strong analytical skills and quantitative background with a Master’s degree or higher in a quantitative field.

Solid understanding of financial mathematics, including cashflow modelling, discounting and fixed income instruments.

Good experience of mathematical modelling and development experience in financial industry.

Good experience of hands-on programming experience in Python

Experience working with large datasets and quantitative analysis

Strong communication skills, with the ability to explain technical topics to non-technical stakeholders

Experience with asset and liability management, liquidity risk, collateral, hedge accounting or regulatory reporting or exposure to IRRBB and ICAAP VaR models

Detailed knowledge of financial products, in particular fixed income products as well as retail banking products, and risk methodologies

Strong background in financial mathematics, asset pricing theory, and statistics

Experience supporting production models in a controlled or regulated environment

Awareness of model risk, controls or governance frameworks

Proactive, good communication skills, team player, creative, result-oriented