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Quantative Risk Analyst, / Hybrid


Quantative Risk Analyst, Dublin/Hybrid

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Date: 8 Apr 2024

Location: Dublin, IE, IE

Company: Allied Irish Bank

Role title: Quantitative Risk Analyst

Location: Molesworth Street, Dublin (Hybrid)

This role is being offered on a permanent, full-time basis.

About the Role: What is Risk Analytics?

Risk Analytics operates within the wider Risk function in AIB, and provides advanced statistical analysis to help inform the Bank in risk-based decision making, and ensuring that the Bank operates in accordance with European banking regulations. This covers a wide range of asset classes, such as International Corporate, Retail, Commercial Real Estate, SME, Sovereign and inter-bank lending.

As an analyst working in Risk Analytics, your projects could include, but are not limited to:

  • 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

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.

As an analyst working in Risk Analytics for a pillar bank in Ireland, your work will make a tangible impact on the stability and performance of AIB and the wider financial system.

Key Responsibilities Include:

We’re looking for someone who would be interested in:

  • 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

The key accountabilities/responsibilities are as follows:

  • 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.

What you will bring:

  • 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.

Life at AIB

At AIB, we have a clear purpose - Empowering people to build a sustainable future. We want to be at the heart of our customers’ financial lives by giving them an exceptional experience. That goes for our employees too.

We are building a culture that breaks the conventions of what our customer and employees expect of a bank.

We are committed to offering our colleagues choice and flexibility in how we work and live. Our hybrid working model enables our people to balance their time between working from home and their designated office, subject to their role, the needs of our customers and business requirements. More details on our hybrid working arrangements and expected office attendance for your role will be provided to you during the recruitment process.

AIB is an equal opportunities employer, and we pride ourselves on being the first bank in Ireland to receive the Investors in Diversity Gold Standard accreditation from the Irish Centre for Diversity. We celebrate diversity and believe in a culture of inclusion where all our employees can succeed. We welcome applications from people of diverse backgrounds and abilities. We are committed to providing reasonable accommodations for applicants and employees. Should you have a reasonable accommodation request please email the Talent Acquisition team at

If you feel you have what it takes, click apply and fill in the online application form. If you would like more information please contact the Talent Acquisition Team at

By when? Closing date is Friday 26th April 2024


Unsolicited CV’s sent to AIB by Recruitment Agencies will not be accepted for this position. AIB operates a direct sourcing model and where agency assistance is required, the Talent Acquisition team will engage directly with our recruitment partners

Job Segment: Bank, Banking, Real Estate, Recruiting, Statistics, Finance, Sales, Human Resources, Data

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