Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Corporate Treasury manages the firm’s liquidity, funding, balance sheet, and capital to maximize net interest income and return on equity through liability planning and execution, financial resource allocation, asset liability management, and liquidity portfolio management. The division is led by the Global Treasurer and collaborates closely with the CFO, the firm’s businesses, Controllers, Operations, and Investor Relations among other groups. This role is ideal for collaborative individuals with strong quantitative analysis skills, an interest in portfolio and liquidity management, and a risk management mindset.

Key responsibilities include designing, implementing, and maintaining quantitative models, tools, and frameworks for Asset Liability Management (ALM) such as Net Interest Margin (NIM) forecasting, Earnings-at-Risk (EaR), and funding cost projections to optimize resources. You will develop stress and scenario analysis frameworks across portfolios, products, and legal entities to assess performance under various market scenarios, identifying and quantifying key risk exposures, concentration risks, convexity effects, and potential vulnerabilities.

Additional duties involve developing and enhancing behavioural models for deposits and other channels, including non-maturity deposit modelling, deposit beta estimation, repricing lags, and volume flow projections under different macroeconomic scenarios and interest rate environments. You will establish rigorous backtesting, model performance monitoring, and data quality frameworks to continuously evaluate model accuracy, identify potential drift, and refine behavioural and forecasting assumptions.

Furthermore, you will develop and uplift models to reflect evolving business needs, maintain model documentation and implementation, and support regulatory inquiries and second-line model validation. The role also requires delivering clear presentations and explanations related to balance sheet management for discussion with senior managers, committees, and key stakeholders.

Experience
- Proven experience in a quantitative finance role with a strong focus on ALM, funding modelling, behavioural modelling, or balance sheet management.
- Solid understanding of fixed income instruments, interest rate derivatives, curve construction methodologies, pricing/hedging strategies, and their application to balance sheet risk management.
- Deep understanding of statistical and econometric modelling techniques such as regression analysis, time-series forecasting, and survival analysis applied to financial products.
- Experience using AI-based tools in development is a plus.

About you
- Excellent written, verbal, and team-oriented communication skills, with the ability to explain complex quantitative concepts to non-technical stakeholders.
- A self-starter who can work independently and thrive in a collaborative, global team environment.
- Collaborative with strong quantitative analysis skills and a risk management mindset.

Qualifications
- Excellent academic background in a quantitative field such as mathematics, physics, statistics, economics, engineering, or computer science, with a preference for Masters and PhDs.
- Strong programming skills in an object-oriented or functional paradigm such as Python, C++, or Java.