Financial Crime Data Science Analyst

An Post; Dublin; On-site; EUR 39,000 - 48,000; Full time

Benefits offered by this job

An Post Company Medical Scheme

PRIP Bonus Scheme

Paid Maternity Leave

Paid Paternity Leave

An Post Employee Assistance Programme

Digital gym with daily scheduled WOrk0

Job summary

An Post in Ireland is seeking a Financial Crime Data Science Analyst to partner with Financial Crime Operations, Compliance, Risk, Technology and business stakeholders to deliver data-driven insights, automated solutions and advanced analytics that strengthen the organisation's financial crime prevention and detection framework.

The role combines expertise in Financial Crime Operations, AML, transaction monitoring and FCCM systems with modern data science techniques, managing analytics

Qualifications

• Honours degree or equivalent in a quantitative field.
• Specialisation in Data Science, AI, ML, Statistics, Financial Crime or Risk Analytics is desirable.
• Professional certifications in AML, Financial Crime, Analytics, Data Science or Risk Management are advantageous.

Responsibilities

• Perform detailed analysis of customer, transaction, screening, and financial crime data to identify trends, anomalies, emerging risks, and potential control gaps.
• Lead transaction monitoring scenario tuning and optimisation activities, including threshold calibration, effectiveness testing, sensitivity analysis, and refinement of detection logic.
• Conduct root cause analysis of financial crime control weaknesses, investigation outcomes, alert volumes, and operational performance indicators.
• Develop analytical insights that support Financial Crime Operations, Risk Management, and Compliance decision making.
• Monitor the effectiveness of financial crime controls and identify opportunities for enhancement through data-driven evidence.
• Support customer risk assessment, behavioural analysis, network analysis, segmentation, and suspicious activity detection initiatives.
• Assist in demonstrating end-to-end understanding and effectiveness of transaction monitoring controls during audits, reviews, and regulatory engagement activities.

Skills

Python

SQL

Data Analytics

CRISP-DM

Machine Learning

Education

Honours degree in Data Science / Statistics / Mathematics / Computer Science / Finance / Risk Management / Economics

Tools

Oracle FCCM

KYC systems

Case management software

Job description

Please note: This is an evolving and developing role and may change over time in line with business needs.

The Financial Crime Data Science Analyst partners with Financial Crime Operations, Compliance, Risk, Technology, and business stakeholders to deliver data-driven insights, automated solutions, and sophisticated analytical capabilities that strengthen the organisation's financial crime prevention and detection framework.

The role combines specialist expertise in Financial Crime Operations, Anti-Money Laundering (AML), transaction monitoring and Financial Crime Compliance Management (FCCM) systems with modern data science techniques. The analyst manages analytics initiatives throughout the full CRISP-DM lifecycle, applying statistical analysis, automation, machine learning, and data engineering practices to improve control effectiveness, optimise monitoring scenarios, identify emerging risks, and enhance operational efficiency.

A key aspect of the role is ensuring the ongoing effectiveness and continuous improvement of financial crime controls through data analysis, scenario optimisation, automation, and evidence-based decision making, while maintaining robust governance, auditability, and regulatory compliance.

Responsibilities

The principal responsibilities of this role include, but are not limited to, the following:

• Perform detailed analysis of customer, transaction, screening, and financial crime data to identify trends, anomalies, emerging risks, and potential control gaps.
• Lead transaction monitoring scenario tuning and optimisation activities, including threshold calibration, effectiveness testing, sensitivity analysis, and refinement of detection logic.
• Conduct root cause analysis of financial crime control weaknesses, investigation outcomes, alert volumes, and operational performance indicators.
• Develop analytical insights that support Financial Crime Operations, Risk Management, and Compliance decision making.
• Monitor the effectiveness of financial crime controls and identify opportunities for enhancement through data-driven evidence.
• Support customer risk assessment, behavioural analysis, network analysis, segmentation, and suspicious activity detection initiatives.
• Assist in demonstrating end-to-end understanding and effectiveness of transaction monitoring controls during audits, reviews, and regulatory engagement activities.

Data Science & Advanced Analytics

• Rigorously follows approved Data Science frameworks, executing, evidencing, and documenting all CRISP-DM lifecycle phases.
• Works in Agile/Kanban delivery environments, participating in stand-ups, reviews, retrospectives, and demonstrations of analytical outputs.
• Translates stakeholder needs into measurable analytical requirements, KPIs, success criteria, monitoring metrics, and decision logs.
• Uses Python, SQL and modern analytics tooling to develop maintainable, version-controlled pipelines and analytical solutions.
• Conducts statistical analysis, data mining and exploratory data analysis to generate descriptive, diagnostic, predictive and prescriptive insights.
• Designs, develops and validates analytical models including anomaly detection, classification, clustering, forecasting, behavioural analytics and risk scoring models.
• Evaluates and communicates model performance, limitations, confidence levels, assumptions, and business implications.
• Supports the responsible use of AI and machine learning solutions within the Financial Crime domain.
• Produces dashboards and reporting solutions that clearly communicate risk indicators, operational performance, control effectiveness and business outcomes.

FCCM Platform & Data Management

• Act as a subject matter expert for Oracle FCCM and associated financial crime data assets.
• Support the ongoing administration, enhancement and optimisation of FCCM modules including Transaction Monitoring, KYC, Enterprise Case Management and Suspicious Activity Reporting processes.
• Support requirements gathering, testing, implementation and continuous improvement of Financial Crime systems and processes.
• Identify, track and support remediation of data quality issues across upstream and downstream systems.
• Develop automated controls, monitoring solutions, alerts and operational reporting capabilities.
• Support integration of Financial Crime data assets within the broader enterprise analytics landscape.
• Maintain comprehensive audit trails for analytics activities, model development, approvals, tuning decisions, deployments and handovers.
• Ensure compliance with GDPR, internal governance standards, financial crime policies, and data management requirements.
• Complete required pre-analysis risk, privacy, ethical and compliance assessments.
• Document methodologies, assumptions, validation outcomes and implementation decisions to support audit and regulatory review.
• Work collaboratively with First and Second Line stakeholders to ensure transparency of analytical approaches and control effectiveness.
• Support internal audits, compliance reviews and regulatory examinations by providing analytical evidence and documentation.
• Identify opportunities to automate manual processes and improve operational effectiveness through analytics and technology.
• Research emerging financial crime analytics techniques, machine learning applications and industry best practices.
• Promote modern analytics capabilities across Financial Crime Operations.
• Contribute to the development and maturity of the organisation's Data Science and Financial Crime Analytics capabilities.
• Prioritise work that advances both financial crime control effectiveness and data science capability development.
• Demonstrate An Post Values and behaviours in your day-to-day work and address behaviour that supports/conflicts with them.

Qualifications

• Honours degree in Data Science, Statistics, Mathematics, Computer Science, Finance, Risk Management, Economics, or a related discipline.
• Specialisation in Data Science, Artificial Intelligence, Machine Learning, Statistics, Financial Crime, or Risk Analytics is desirable.
• Professional certifications in AML, Financial Crime, Analytics, Data Science or Risk Management are advantageous.

Experience

• 3–5 years' experience in Financial Crime Analytics, AML Operations, Data Analytics, Data Science, Risk Analytics, or a related field.
• Demonstrated experience working with transaction monitoring, customer screening, case management or financial crime systems.
• Experience managing projects through the full CRISP-DM/Agile lifecycle including governance and documentation requirements.
• Hands-on experience with Python and SQL for analytics, automation and data engineering.
• Experience working with Oracle FCCM/Compliance Studio or equivalent financial crime platforms.
• Experience performing scenario tuning, effectiveness assessment and optimisation of monitoring controls.
• Experience working within Agile/Kanban environments.
• Experience producing analytical reporting, dashboards and actionable business insights.
• Experience supporting audits, regulatory reviews and governance activities.
• Proven ability to communicate technical concepts and analytical findings to both technical and non-technical stakeholders.

Critical Competencies (The following competencies are critical to the delivery of results and/or to superior performance in this role:)

• Problem Solving & Analysis
• Attention to Detail
• Technical & Professional Expertise
• Communication and Influencing Skills
• Teamwork

Salary range starting from €43,319 .Placement within the range reflects experience, skills, proficiency in the role, and internal alignment. Progression over time is linked to performance, development, and expansion in role scope.

• An Post Company Medical Scheme
• PRIP Bonus Scheme
• Paid Maternity Leave
• Paid Paternity Leave
• An Post Employee Assistance Programme
• Digital gym with daily scheduled workouts
• Secure on-site bicycle parking & Cycle to Work Scheme
• Tax Saver Travel Pass
• City Centre location

At An Post we appreciate the value that diversity brings and believe our workforce should be reflective of the customers and communities we serve. That is why we actively welcome applications from people from all backgrounds, and do not discriminate based on gender, age, race, religion, marital status, sexual orientation, disability, membership of the Travelling community, or family status. We are committed to having an inclusive workplace where every employee feels they belong. If you require accommodations to be made during the recruitment process, or have questions relating to accessibility, please contact [e-mail]

About An Post

An Post is one of Ireland’s leading organisations, offering financial and postal services as well as being a trusted gateway to government services. We are transforming from the old world of traditional letters and cash to the new digital world of e-commerce parcels and financial services.

An Post’s core purpose — to act for the common good, improving the lives of people in Ireland, now and for generations to come — is aligned with the United Nations Sustainable Development Goals, putting sustainability at the centre of everything we do. Corporate Social Responsibility plays a pivotal role at An Post as we focus on developing long-term sustainability. Diversity and Inclusion are also embedded in our strategy, as we continuously evolve to be representative of our employees and the communities we serve. Read more about our strategy and our progress today!