About the role
AI summarisedAs a member of the Fraud Detection Analytics team, you will play a pivotal role in protecting customer assets by applying data analytics and machine learning models to detect and prevent fraudulent activity. This role involves managing data integrity, developing analytical insights from complex datasets, optimizing fraud detection rules, and communicating findings to drive business impact across cross-functional teams.
BankingOnsite
Key Responsibilities
- Manage and maintain data sources, ensuring the integrity and accuracy of data fueling fraud detection models.
- Develop and execute data analysis plans to extract insights from large and complex datasets, uncovering hidden patterns indicative of fraudulent activity.
- Optimize fraud detection rules by tweaking or deactivating existing ones to reduce false positives and streamline the rule engine.
- Create and deliver compelling data visualizations and reports to communicate findings to stakeholders, enabling swift action against fraud.
- Collaborate with cross-functional domain experts on high-impact projects to drive business value through data-driven solutions.
- Maintain proper documentation of business requirements and data management definitions for process clarity.
Requirements
- Proven ability to apply data analytics and machine learning concepts in a financial services context.
- Experience working with large and complex datasets.
- Strong analytical skills to uncover anomalies and patterns in data.
- Ability to translate technical findings into actionable business insights for non-technical stakeholders.
- Commitment to maintaining high standards of data integrity and accuracy.
- Proactiveness in staying abreast of industry best practices in fraud detection.