Quantative Risk Analyst, Dublin/Hybrid
Allied Irish Banks
- Dublin
- Permanent
- Full-time
- Point-in-time performance analysis for loss provisioning
- Long-term (“through-the-cycle”) economic capital analysis
- Algorithms for automated lending decisioning
- Macroeconomic scenario forecasting and stress testing
- Simulations of the macroeconomy for systematic risk
- Long-term studies on the effect of Climate Change on credit risk and sustainability
- Estimation of risk-based loan pricing
- Development of behavioural and portfolio models to support business decision making and estimation of credit movements in line with IFRS9, IRB and stress testing standards and internal development policies. This includes but is not limited to: Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD) models.
- Performing segmentation analysis and calibration of models
- Contributing to the standards and methodologies required to deliver these models
- Extracting, transforming, and cleaning the data required for modelling
- Engaging with customer facing Business to understand how our models can support their decision making
- Engaging with regulatory bodies as part of the on-going cycle of regulatory review of our models
- Analysis and Investigation: Undertake various complex data analyses, investigations and/or modelling of business issues to improve the management, services and products of the bank.
- Digital protection: Access / utilise bank data within the policies and frameworks required by AIB.
- Predictive Model Development: Take a role in building predictive models that are focussed on impacting core business elements, such as capital requirements and loss expectations.
- Data insights: Perform in exploratory and ad-hoc data analysis with a view to generating insights and using this to deliver actionable recommendations to the Business.
- Risk Segmentation Analysis: Creating segmentations that allow us to better understand the risks present in our lending portfolio and what we can do to better manage the risks.
- Show problem solving skills with capability to defend your decisions from challenge.
- 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.).
- 2 or more years of experience with SAS or SQL programming – experience in an alternative programming language would be considered (e.g. R, Python, Matlab).
- Curiosity and inventiveness. Good problem-solving skills with capability to defend their decisions from challenge both on a technical and business front.
- Candidates must be fully authorised to work in Ireland.