This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Join us as a Fraud Technical Data Analyst where you’ll play a critical role in designing and delivering data-driven solutions that support fraud detection, prevention, and reporting. This technical role blends evaluative depth with strategic insight, enabling collaboration across fraud, data technology, and business teams to protect customers and the organisation from financial crime.
Job Responsibility:
Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement
Designing and building data pipelines to automate data movement and processing
Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI
Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements
Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs
Requirements:
Capturing and translating business needs into scalable technical solutions with stakeholders
Using SAS and SQL for data exploration, reporting, and technical processing, working with large datasets
Experience with different data management techniques including ETL, CDC, and data warehousing tooling
Nice to have:
Experience in fraud prevention, detection or investigation within the financial services sector
Certifications in SAS, AWS, or Python, and knowledge of ETL and data warehousing
Data visualisation with Tableau or Power BI, and fraud experience in financial services
Working across time zones and applying knowledge of Spark, Databricks, and data compliance