London/Hybrid, 3 days in the office
My client are a Global Banking organisation seeking a highly skilled Data Scientist to join their EMEA Financial Crime Operations team. You will work within the Intelligence & Analytics function, responsible for enhancing the effectiveness of transaction monitoring and sanctions screening systems. This is a hands‑on, data‑driven role with a focus on leveraging advanced analytics, optimisation techniques, and model validation to strengthen financial crime detection across multiple jurisdictions.
This role will suit an expert in Financial Crime Analytics or a Data Scientist with background in transaction monitoring and sanctions.
Key Responsibilities:
- Lead a specialist analytics team to develop, optimise, and enhance segmentation, tuning, and monitoring logic in transaction monitoring and sanctions screening programs.
- Coordinate and implement detection scenarios to identify potential financial crime activity.
- Support the design, tuning, and optimisation of automated monitoring and sanctions screening models, ensuring high alert quality and efficiency.
- Contribute to the development and validation of models, including scenario calibration, segmentation logic, and optimisation frameworks.
- Collaborate with regional analytics teams to share learnings and implement global improvements in financial crime detection.
- Assist in updating policies, procedures, and governance frameworks related to transaction monitoring and sanctions screening activities.
- Translate complex analytical insights into actionable recommendations for operational teams, senior management, and regulators.
- Oversee model validation, memorialise assumptions, and ensure regulatory alignment with AML, sanctions, and financial crime compliance standards.
Key Skills/Experience:
- Proven track record in transaction monitoring and financial crime detection, with experience in sanctions screening highly desirable.
- Strong experience in a global banking organisations, consultancy, or regulatory environment, with strong analytical and problem‑solving skills.
- Hands‑on experience with data engineering and data science techniques: building scalable analytics pipelines, model development, and optimisation frameworks.
- Transaction monitoring system experience would be advantageous such as Actmize, Fiserve AML, SAS AML, FICO TONBELLER, Oracle Mantas.
- Advanced analytical tools and programming languages, experience of Python is essential, advantageous to have exposure to SQL, Spark, Databricks, Snowflake, Pandas, or similar.
- Strong knowledge of financial crime regulations, including AML, sanctions, and monitoring requirements across EMEA jurisdictions.
- Excellent written and verbal communication skills, with the ability to present complex analytical insights clearly to senior management and regulatory bodies.
- Degree or equivalent industry-standard qualification in a quantitative, technical, or finance‑related discipline.
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