Dublin-Based Quantitative Risk Analyst, Model Validation

AIB; Dublin; Hybrid; EUR 55,000 - 75,000; Full time

Benefits offered by this job

Pension Scheme

Healthcare Scheme

Variable Pay

Employee Assistance Programme

Family leave

Volunteer days

Job summary

AIB is seeking a quantitative risk analyst to support independent validation of Pillar 1/2 and IFRS9 ECL models. You will use statistical techniques and data analytics to review, challenge, and provide independent opinions on model development.

Office-centric hybrid role in Dublin, with 3 days in the office; 1+ years' experience in analytics; SAS required; knowledge of SQL, R or Python beneficial; join a diverse team.

Qualifications

• Relevant third level or postgraduate analytical qualification.
• 1+ years’ experience in a quantitative analytics role, preferably credit risk.
• Knowledge of regulatory env (IRB/IFRS9) and EU implementation is a plus.
• Experience applying statistical tools to support data-driven decisions.
• Ability to challenge established thinking and articulate opinions.
• SAS is required; SQL, R or Python are advantageous.

Responsibilities

• Review and challenge bank models using statistical techniques and data analytics.
• Provide robust challenge to model development teams to ensure robustness and regulatory compliance.
• Deliver validation activities per CRR/EBA guidelines while taking ownership of work.
• Prioritise tasks to meet deadlines and adapt to a changing environment.
• Learn from team members and grow within the role.

Skills

Statistical analysis

Data analytics

Problem solving

Communication

Education

Analytical degree (3rd level)/postgraduate

Tools

SAS

SQL

R

Python

Job description

AIB is seeking a quantitative risk analyst to support independent validation of Pillar 1/2 and IFRS9 ECL models. You will use statistical techniques and data analytics to review, challenge, and provide independent opinions on model development.

Office-centric hybrid role in Dublin, with 3 days in the office; 1+ years' experience in analytics; SAS required; knowledge of SQL, R or Python beneficial; join a diverse team.