Data Scientist, Economic Crime Hub

Overview

As a Data Scientist in the Economic Crime Hub, you design data-driven tools to prevent fraud and reduce customer harm. You collaborate with Fraud, Engineering and Data teams to translate challenges into measurable, data-led solutions and promote a data-driven culture across business stakeholders. You develop scalable, ethical fraud detection approaches and monitor their effectiveness in a regulated environment. This role offers the opportunity to impact fraud prevention at scale while working within an Agile, cross-functional context.

Responsibilities

• Translate fraud and scam challenges into analytical questions and measurable outcomes
• Build reusable data pipelines and deploy scalable solutions in an Agile setting
• Select, train and validate ML models and AI applications balancing detection with customer impact
• Monitor model performance, data quality and drift; recommend corrective actions
• Investigate emerging fraud patterns and improve processes with governance and audit in mind

Key requirements

• STEM academic background
• experience with statistical modelling and machine learning for fraud or rare-event risk
• ability to translate data insights into business actions
• programming language skills and software engineering fundamentals
• cloud applications experience
• ability to visualise data and communicate insights to stakeholders

• stakeholder collaboration
• clear communication
• problem solving
• statistical modelling
• machine learning
• programming language and software engineering fundamentals

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