Job Description
We’re working with a leading global financial institution seeking an experienced ALM Quantitative Analyst (AVP level) to join their Treasury Quantitative Analytics team in London. This is a high-impact role supporting Treasury Finance by developing statistical models to forecast behavioural asset and liability balances—key to managing interest rate risk.
Key Responsibilities:
* Develop and implement quantitative models for asset-liability forecasting and interest rate risk management.
* Utilise advanced econometric and statistical techniques such as time series analysis and regression modelling.
* Translate complex technical concepts for both technical and non-technical stakeholders.
* Write robust, production-ready Python code and partner with technology teams to operationalise models.
* Ensure models are compliant with internal governance and model risk frameworks.
* Provide ongoing model validation, documentation, and performance monitoring.
Ideal Candidate Will Have:
* Strong background in ALM or Treasury modelling, particularly behavioural balance forecasting.
* Deep knowledge of statistical/econometric methods.
* Solid Python programming skills and experience handling large datasets.
* Clear and confident communicator, able to bridge the technical and business gap.