Fraud Data Scientist.

AIB; Dublin; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Market leading Pension Scheme

Healthcare Scheme

Variable Pay

Employee Assistance Programme

Family leave options

Two volunteer days per year

Job summary

AIB is seeking a technically strong Fraud Data Scientist to join the fraud decisioning capability. You will apply data science techniques to fraud detection and prevention in financial transactions, including payments and transfers, while supporting analytic insight across the fraud environment.

You will work with cross-functional teams, develop predictive models, perform A/B testing, and translate data into business-focused insights for stakeholders.

Qualifications

• 3–5 years’ experience with ML-based detection systems (development, validation, deployment, post-live monitoring).
• In-depth knowledge of ML algorithms, especially tree-based models and anomaly detection KPIs.
• Hands-on expertise in SQL, Python, and Big Data tools such as Databricks.

Responsibilities

• Review and enhance anomaly detection in payment systems, including business rules and ML models.
• Transform new data streams into fraud risk signals for rules and models.
• Understand the ML lifecycle from exploration to deployment.

Skills

ML models

SQL

Python

Databricks

Fraud domain knowledge

Anomaly detection

Tools

Featurespace

TSYS

Neo4j

TigerGraph

Job description

At AIB, our values guide how we work and how we support each other. We’re looking for someone who puts Customer First, takes initiative and Owns the Outcome, and is always looking for ways to Eliminate Complexity. You’ll treat colleagues and customers with fairness and Show Respect, and you’ll thrive in a culture built on collaboration where we Be One Team to deliver meaningful impact.

Location/Office Policy: Central Park, Dublin 18 - 3 days per week in office

• Would you like to play a leading role in a team whose ambition is to become a world class fraud function, exceptional at developing talent and turning information into insights?
• Do you enjoy collaborating with cross functional teams and influencing business direction with data-backed evidence?
• Do you activelyseek opportunities for innovation and continuous improvement?

What Is The Role

We are looking for a technically strong Fraud Data Scientist to join the fraud decisioning capability within AIB. This role will focus on applying data science techniques to fraud detection and prevention in financial transactions, including payments and transfers, while also supporting forward-looking analytical insight across the fraud environment

Key Accountabilities

• Apply domain knowledge in financial fraud to review and enhance existing anomaly detection in payment systems, including business rules and machine learning models.
• Support the transformation of new data streams into fraud risk signals to be used by rules and models.
• Develop a thorough understanding of the data science lifecycle including data exploration, preprocessing, feature engineering, modelling, validation, and deployment.
• Design, build, and maintain predictive models, including decision trees, random forests, and gradient-boosted trees, with a low-level understanding of their algorithms and functioning.
• Conduct A/B testing and other validation techniques to ensure the accuracy and reliability of payment rules and models.
• Communicate complex data insights to non-technical stakeholders through clear and actionable reporting.
• Collaborate with cross-functional teams and support data-driven improvements through exploration, feature engineering, and model enhancement

What You Will Bring

• 3–5 years’ experience working with machine learning-based detection systems including development, validation, deployment, and post-live monitoring.
• In-depth knowledge of machine learning algorithms, particularly tree-based models, and anomaly detection performance KPIs.
• Hands-on expertise in SQL, Python, and Big Data tools such as Databricks.
• Understanding of fraud typologies such as card fraud, payment fraud, account takeover, and mule activity would be desirable.
• Exposure to fraud platforms such as Featurespace, TSYS, or similar detection systems is desirable; familiarity with graph database technologies such as Neo4j or TigerGraph is a plus.
• Ability to translate data into clear, business-focused insights and work effectively with a wide range of stakeholders.

Why Work For AIB

We are committed to offering our colleagues choice and flexibility in how we work and live and 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.

Some Of Our Benefits Include

• Market leading Pension Scheme
• Healthcare Scheme
• Variable Pay
• Employee Assistance Programme
• Family leave options
• Two volunteer days per year

Key Capabilities

• Customer First
• Ensures Accountability
• Collaborates
• Eliminates Complexity
• Data Analysit
• Investigating & Reporting

If you are not sure about your suitability based on any aspects of the role advertised, we encourage you to please contact the Recruiter for this role, Sarah Lyons, at [e-mail] for a conversation.

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 are committed to providing reasonable accommodations for applicants and employees. Should you have a reasonable accommodation request please email the Talent Acquisition team at [e-mail]

Application deadline : 4th September 2026