Description:
The IRB Model Development Team are responsible for the design and delivery of predictive credit risk measurement models relating to the Bank’s Pillar 1 capital PD, LGD and EAD models. These models are used to determine the level of risk associated with individual borrowers and drive the determination of the Bank’s regulatory capital requirements. The team is currently undertaking a multi-year redevelopment of all IRB models followed by the rollout of new IRB models, which represents a key strategic objective for the bank. The role involves working closely with our colleagues across the Business, Credit Risk, and the Chief Data Office.
Key Accountabilities.
- Analysis & investigation: Undertake and guide junior data scientists in various complex data analyses, investigations and/or modelling of business issues to improve the management, services, and products of the bank.
- Predictive model development: Take a leading role in building predictive models that are focussed on core business elements, such as automated decisioning, capital requirements and loss expectations.
- Data insights: Perform and guide junior data scientists in exploratory and ad-hoc data analysis with a view to generating insights and using this to deliver actionable recommendations to the Business.
- Expert advice: Provide specialist advice to the business with an emphasis on the impact and application of risk management requirements.
- 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.
- Leadership: Mentoring and guidance for junior data scientists. Also, there will be responsibility for reviewing work carried out by junior team members.
- Digital protection: Access / utilise bank data within the policies and frameworks required by AIB.
What you Will Bring;
- Minimum 3 years’ experience in a model monitoring, 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 consider (e.g., R, Python, Matlab). Advanced experience in extracting, transforming, and cleaning data for modelling purposes.
- Familiarity with data visualisation tools such as QlikView, Power BI, SAS VA or Tableau.
- Strong ability to build relationships and communicate with key stakeholders, Curiosity, and inventiveness. Good problem-solving skills with capability to defend their decisions from challenge both on a technical and business front.