2 x Quantitative Analyst/Risk Manager (QRM) - London - Bank

QRM - Quantitative Risk Modelling - Risk - Analytics - Quant - Models - Python

Quantitative Analyst/Risk Manager required by large Investment Bank, based in London (Hybrid Home working) to work within the Enterprise Risk Management - Centralised Modelling, Analytics & Operations (CMAO) area.

As part of a global remidiation programme they are executing a high-priority strategic enhancement initiative for one of its significant European legal entities. The programme is focused on strengthening how the firm measures, explains, and governs:
* Interest Rate Risk in the Banking Book (IRRBB), and Credit Spread Risk in the Banking Book (CSRBB).

Responsibilities
1. Building and enhancing the analytics used to quantify IRRBB/CSRBB in QRM (Quantitative Risk Management)
2. Producing the materials required to demonstrate that those analytics are sound, consistently applied, and understood by senior management.

This work is high-visibility and touches Risk, Treasury, Model Risk Management, Finance, and senior stakeholders at both legal-entity and corporate level

Skills/Knowledge required:

• 5+ years' experience in banking or financial services with direct exposure to IRRBB and/or CSRBB, asset-liability management, Treasury risk, or balance sheet risk.
• Proven hands-on experience with QRM (vendor product), including configuring calculations, running sensitivities and scenario-style projections, and interpreting EVE/NII results.
• Ability to connect risk measurement to management action: limits, stress testing, funding/liquidity considerations, and capital/ICAAP-style discussions.
• Expericne with Python, R, or similar for analysing model outputs, checking reasonableness, and producing supporting analysis.
• Familiarity with European IRRBB/CSRBB expectations (eg EBA/ECB) and how those expectations typically show up in governance, model review, and senior escalation.
• Able to write clearly, to the standard required for model review/validation/senior committee packs.
• Comfortable working under time pressure with multiple stakeholders and parallel deliverables.

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