Treasury Quantitative Analyst (VP)

Empirical Search
Greater London, England
14 months ago
Applications closed

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Finance Data Architecture Lead - Insurance

Experis London, United Kingdom
Hybrid
Posted
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Role Description

Design analytics and modelling solutions to complex business problems using domain expertise Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation team Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users Demonstrate conformance to all the Bank’s Enterprise Risk Management Policies, particularly Model Risk Policy Ensure all development activities are undertaken within the defined control environment

Role Requirements

Industry experiences supporting stakeholders to manage interest rate risk and implementing capabilities required for cashflow generation of interest rate flow products including swap, bonds, repos, deposit; discount and forward curves Expert coding skills in Python, with experience developing and delivering analytics within a team Excellent communication skills, including the ability to discuss technical matters with a non-technical audience Asset Liability Management Quant with experience supporting Interest rate risk of banking book (IRRBB) Systems engineering knowledge, including development of distributed systems

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Where to Advertise Data Science Jobs in the UK (2026 Guide)

Where to advertise data science jobs UK in 2026: the specialist boards, communities and channels that actually reach senior and lead data science talent. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.