Manager, Credit Risk Analytics and Modelling

Credit Risk Modelling Manager - J12780 - up to £70K - Manchester or Leeds/Hybrid

Encompassing skills across regulation and finance with a deep analytics capability. As a member of the Credit Risk Analytics team, your role will include:

Improve and develop credit model capabilities focussing on IFRS9, IRB and stress testing approaches across the full range of credit products.
Providing credit measurement modelling and analytics
Supporting 1st Line teams with the build of new models or improvement/review of existing models, support to 2nd Line oversight/model review functions or to 3rd Line Internal Audit teams
Designing and improving credit measurement ecosystems; for example practices around insight into movements, data, controls, model risk management, model monitoring and maintenance, reporting and external disclosure
Audit of IFRS9 and assurance of RWA through challenge of methodological approaches and quality of implementation to identify material weaknesses
Credit Risk projects inc. acquisition due diligence, stress testing and Quality Reviews
Leading a small team of modelling specialists
Sskills and professional experience

Credit modelling skills and experience in the development, delivery and/or validation of credit risk models under one or more of the IFRS9, IRB and forecasting/stress testing regimes
Experience of the management of credit financials, associated governance and stakeholder perspectives
Have worked within the financial services industry and the credit fundamentals of different asset classes
Management and leadership skills
Skills with modelling software such as SAS, SQL, MS Excel (including VBA), Python, R
Ability to think creatively, generate innovative ideas, challenge the status quo and deliver effectively
To find out more and to apply for this role in London, please contact Sue@Datatech Analytics today on (phone number removed).

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Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)