Quantitative Risk Manager, Decision Analytics & Insights

This role is positioned within the Decision Analytics Team in Risk Analytics as a Quantitative Risk Manager. Risk Analytics is part of the Risk Function, this is an independent, second line of defence function that monitors, controls, and supports risk‑taking activities across AIB. The purpose of the Risk Function is to provide advice and guidance in relation to risk while providing independent oversight and reporting on AIB's risk profile. The Risk Function's main objective is to ensure AIB has a robust risk‑management framework and culture in place to ensure risks are taken within the risk appetite set by the Board, in support of AIB's customer franchise and social responsibility. This role is in the Decision Analytics and Insights Model Development Team in Risk Analytics. They are responsible for the quantitative modelling used for decision automation, and the credit grading of standardised portfolios.

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• Leading the development of Grading models to support business decision making, risk management and estimation of regulatory capital requirements in line with internal development standards and policies. This includes but is not limited to: Application and Behavioural Scorecards, Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD) models;
  
• Managing the team involved in the development of Grading models, guiding them in the development of technical skills as well as core behavioural competencies;
  
• Engaging with stakeholders across the Business, Finance and Risk to ensure that models can facilitate business needs while meeting regulatory requirements and provide enhancements to the application of risk management within the Bank;
  
• Engaging with regulatory bodies and internal second and third line of defence assurance teams as part of the on‑going cycle of review of our models;
  
• Contributing to the development and refinement of standards, methodologies and toolsets required to deliver these models and ensuring they are embedded within the development team;
  
• Contribute to the credit decisioning strategies which support the automation of Retail and non‑Retail credit decisions throughout the credit lifecycle;
  
• Performing exploratory and ad‑hoc data analysis to generating meaningful customer or portfolio insights;
  
• Extracting, transforming, and cleaning the data required for modelling and analysis purposes;
  

Credit risk is a dynamic, ever‑evolving field and working for Risk Analytics will place you at the vanguard of quantitative risk analysis, regularly implementing the latest published methodologies and creating bespoke in‑house solutions to challenging problems, as part of an experienced team where you will receive support and training to help you reach your potential.

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• Minimum 5 years' experience in a model development or model validation role. Examples include: IRB; IFRS 9; loss forecasting; stress testing or economic capital modelling; propensity modelling; or a combination thereof. A bachelor's degree in a quantitative analytical discipline (2.1 or higher), e.g. mathematics, applied mathematics, physics, statistics, engineering, econometrics. (Confirmation will be sought if successful for the role.);
  
• Ideally have Advanced level of SAS or SQL programming - an equivalent level in an alternate programming language would be considered (e.g. R, Python, Matlab). Advanced experience in extracting, transforming, and cleaning data for modelling purposes;
  
• Strong understanding of the regulatory requirements relating to the development of grading models;
  
• Experience writing technical documents that meet internal and regulatory standards;
  
• Experience in engagement with regulatory or audit bodies;
  
• Experience training and managing the day‑to‑day tasks of junior team members;
  
• Strong ability to build relationships and communicate with key stakeholders in model development or validation activities;
  
• Curiosity and inventiveness. Good problem solving skills with capability to defend their decisions from challenge both on a technical and business front.