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Quantitative Risk Analyst, Model Validation, Dublin

Date: 21-Nov-2020

Location: Dublin, IE

Company: Allied Irish Bank

Role: Quantitative Risk Analyst, Model Validation


Location: Burlington Rd, Dublin / Remote Working Available


Are you a risk analyst who is seeking to progress in your career?

Are you interested in how data and analytics can help us to back our customers and ensure the success and stability of the bank?


We’re looking for someone who:

  • Uses statistical techniques and data analytics tools to review and challenge the models being used within the bank;
  • Challenges the modelling teams and business areas in the bank to assure and improve the bank’s models;
  • Actively seeks opportunities to learn from other team members and to grow within the role;


Who are we?

We’re AIB. A strong Irish bank packed with purpose - to back our customers to achieve their dreams and ambitions. That goes for our employees too. We’re made of small teams where you have the chance to shine.


Why join us?

We are excited about how we have changed our focus. We want to be at the heart of our customers’ financial lives by giving them an exceptional experience. We are building a culture that breaks the conventions of what our customer and employees expect of a bank.


Does this sound like something that you want to be part of?


About you:

  • Relevant third level qualification or Postgraduate qualification in an analytical discipline, e.g. mathematics, applied mathematics, physics, statistics, engineering, econometrics, actuarial science;
  • At least 3 years’ experience in a quantitative role, credit risk analytics experience is preffered but other relevant experience will also be considered e.g. market risk, fraud analytics, marketing analytics, statistician, economist;
  • A  good knowledge of the regulatory environment as it applies to credit risk, including one of the following - IRB or IFRS9;
  • A strong interest in applying statistical tools and techniques in a practical setting to help the bank in ensuring models and data driven decisions are robust and can be relied upon;
  • A natural inclination to challenge established ways of thinking and an ability to articulate your opinion;
  • Strong knowledge of analytics languages (e.g. SAS, R, SPSS, Matlab or Python) and SQL


If you feel you have what it takes, Click Apply and fill in the online application form. If you would like more information Donal O'Sullivan from the Talent Acquisition Team can help. You can contact him on 087-3328638 or email


By when?  Closing date is 4th December 2020

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