Analyst

Albany Beck; Dublin; On-site; EUR 70,000 - 100,000; Full time

Job summary

Albany Beck is seeking a Financial Crime Data Science Analyst to enhance analytics and monitoring for a Financial Services client. You will combine data science, AML, and technology to improve controls, tune transaction monitoring and boost operational efficiency.

The role involves building models, automating data pipelines, and delivering insights to risk, compliance and technology teams while leveraging Oracle FCCM and BI tools.

Qualifications

• 3–5 years in data analytics, data science or financial crime analytics.
• Proficiency in Python and SQL for analytics and automation.
• Experience with AML or Financial Crime controls and monitoring.
• Experience tuning transaction monitoring scenarios and threshold calibration.
• Strong statistical analysis, data mining and exploratory data analysis.
• Experience building analytical models: anomaly detection, classification or clustering.
• Ability to translate insights into clear business recommendations.
• Familiarity with governance, documentation, audit trails and data quality.

Responsibilities

• Analyse customer, transaction, screening and Financial Crime data to identify trends and risks.
• Lead transaction monitoring scenario tuning and optimization, including calibration and testing.
• Develop automated data pipelines and analytical solutions using Python and SQL.
• Produce analytics reports and dashboards with Power BI or Fabric.
• Support internal audit, Compliance reviews and regulatory examinations.
• Collaborate with Financial Crime Operations, Compliance, Risk and Technology teams.
• Apply AI/ML responsibly within Financial Crime analytics and monitoring.

Skills

Python

SQL

Data mining

Statistical analysis

Anomaly detection

Classification

Education

Degree in Data Science or related field

Tools

Oracle FCCM

Power BI

Microsoft Fabric

Job description

Albany Beck is a Financial Services consultancy specialising in Technology, Risk & Compliance, Cyber Security, Change & Transformation, Operations and Data. We partner with leading banks, asset and wealth managers, insurers and other financial institutions across the UK and Ireland, providing high-quality consultants to support complex transformation, regulatory and technology programmes.

Client Deployment Role Description

Albany Beck is looking for a Financial Crime Data Science Analyst to work with one of our Financial Services clients, supporting the continued development and optimisation of their Financial Crime analytics and monitoring capabilities.

This role sits at the intersection of Financial Crime, AML, Data Science and Technology, working closely with Financial Crime Operations, Compliance, Risk and Technology teams.

The successful candidate will use data analytics, statistical techniques, automation and machine learning to improve the effectiveness of Financial Crime controls, optimise transaction monitoring scenarios, identify emerging risks and improve operational efficiency.

A key focus will be supporting and optimising transaction monitoring and Financial Crime systems, including Oracle FCCM or equivalent platforms.

Key Responsibilities

• Analyse customer, transaction, screening and Financial Crime data to identify trends, anomalies, emerging risks and potential control weaknesses.
• Support Financial Crime Operations, Compliance and Risk teams with data-driven insights and recommendations.
• Lead transaction monitoring scenario tuning and optimisation, including threshold calibration, sensitivity analysis and effectiveness testing.
• Analyse alert volumes, investigation outcomes and control performance to identify areas for improvement.
• Conduct root cause analysis on Financial Crime control weaknesses and operational issues.
• Support customer risk assessment, behavioural analysis and suspicious activity detection initiatives.
• Use Python and SQL to build analytical solutions, automated processes and maintainable data pipelines.
• Conduct statistical analysis, data mining and exploratory data analysis across Financial Crime datasets.
• Develop and validate analytical models including anomaly detection, classification, clustering, forecasting, behavioural analytics and risk scoring.
• Support the responsible use of AI and machine learning within Financial Crime.
• Act as a key point of contact for Oracle FCCM, supporting administration, optimisation and continuous improvement of Financial Crime systems.
• Identify and support the remediation of Financial Crime data quality issues.
• Develop automated controls, monitoring solutions, alerts and operational reporting.
• Produce analytical reporting and dashboards using tools such as Power BI and Microsoft Fabric.
• Maintain appropriate documentation, audit trails, model validation records and analytical evidence.
• Support internal audit, Compliance reviews and regulatory examinations where required.
• Work closely with First and Second Line stakeholders to ensure transparency and effectiveness of Financial Crime controls.
• Identify opportunities to automate manual Financial Crime processes and improve operational efficiency.
• Contribute to the continued development of Financial Crime Analytics and Data Science capabilities.

Key Skills & Experience

• 3–5 years' experience within Data Analytics, Data Science, Risk Analytics or Financial Crime Analytics.
• Strong experience using Python and SQL for analytics and automation.
• Experience working with transaction monitoring, AML or Financial Crime controls.
• Experience performing transaction monitoring scenario tuning, threshold calibration and control effectiveness testing.
• Strong statistical analysis, data mining and exploratory data analysis experience.
• Experience developing analytical models such as anomaly detection, classification, clustering or risk scoring.
• Ability to analyse large Financial Crime datasets and translate findings into clear business insights.
• Experience working through the full analytical lifecycle, ideally using CRISP-DM, Agile or similar methodologies.
• Strong understanding of governance, documentation, auditability and data quality requirements.
• Strong stakeholder management skills with the ability to work across Financial Crime Operations, Compliance, Risk and Technology teams.
• Experience with Oracle FCCM / Compliance Studio or another Financial Crime monitoring platform.
• Previous experience within AML Operations or Financial Crime Compliance.
• Experience with Power BI and Microsoft Fabric.
• Experience working with customer screening, case management and Financial Crime monitoring systems.
• Knowledge of AI and machine learning applications within Financial Crime.
• Experience working within Agile or Kanban environments.
• Degree in Data Science, Statistics, Mathematics, Computer Science, Finance, Risk Management, Economics or a related discipline.

Personal Attributes

• Strong analytical and problem-solving skills.
• High level of attention to detail.
• Strong technical capability combined with an understanding of Financial Crime.
• Able to explain complex analytical findings clearly to technical and non-technical stakeholders.
• Comfortable working collaboratively across multiple teams and functions.
• Strong continuous improvement mindset with an interest in automation and emerging technology.
• Able to work within a highly governed and regulated Financial Services environment.