Data Scientist (m/w/d) at EVERIENCE

As an Insights Data Scientist – Transaction Monitoring, you will play a key role in delivering data-driven insights and building automated data pipelines and workflows based on large-scale transaction data from millions of customers within a banking environment. Your work will support colleagues in making better-informed decisions to detect and prevent financial crime. Preventing money laundering and terrorist financing is a critical responsibility within the banking sector and society at large. Financial institutions play an essential role in this area, relying on analytical professionals who are curious, detail-oriented, and motivated to explore data, patterns, and customer behaviour to identify unusual or potentially suspicious activities. Together with your team, you will contribute to generating insights into the current Transaction Monitoring (TM) systems and support their continuous improvement. This role requires a strong mix of technical expertise and analytical thinking, combined with the ability to clearly visualise and communicate findings. Your work will help operational teams focus on high-quality alerts and improve overall efficiency, contributing directly to the effectiveness of financial crime detection. Team Composition:  You will be part of a multidisciplinary team of around 6–10 professionals, including a Product Owner, Scrum Master, Data Scientists, and Data Analysts, working in an agile setup. Your Key Responsibilities: • Develop and enhance data pipelines for analyses such as tuning, lookbacks, and impact assessments, efficiently combining complex transaction monitoring components • Perform end-to-end analyses, from understanding business requirements and coding to visualisation and presenting insights to stakeholders • Design and develop production-ready dashboards (front-end and back-end) to support rule optimisation, development, and daily monitoring insightsExamples of Your Work: • Assessing the impact of parameter changes in transaction monitoring models on detection effectiveness and operational efficiency • Improving workflows to enable more scalable and flexible tuning of monitoring rules • Building and deploying dashboards, such as: • Rule performance dashboards to optimise detection logic • System-wide monitoring dashboards providing overall insights • Transaction-focused dashboards to support new rule development