AML Detection Data Scientist with French

Job description

We are looking within the Anti Money Laundering team for a Data Scientist in charge of the calibration of Financial Security Scenarios, whose function mainly consists of ensuring the optimization of the Group’s framework for fighting financial crime through its Transactions Monitoring Systems, by ensuring proper and correct calibrations of associated scenarios. The calibration of a transaction monitoring scenario is the process of setting thresholds to target suspicious transactions or behavior.

A scenario is a rule or algorithm designed based on the money laundering/terrorism finance risks associated with transactions or accounts, which is used to detect unusual transactions or behaviors by triggering alerts that are further investigated to detect Money Laundering/Terrorism Finance. Thus, the role of the Data Scientist is to perform recurrent and ad-hoc studies of financial crime scenarios, reviewing their outputs, and setting new thresholds for their parameters .

Specifically, you will be required to:

• Calibration of Financial Crime Compliance Scenarios, employing statistical analysis and Group’s models.

Data analysis

• extraction of data, cleaning, analyzing, visualizing to support conclusions and support decision-making.
• Perform ad-hoc studies relevant for the optimization of financial security scenarios, the number of generated alerts.
• Analyzes the pertinence of generated alerts and proposes new thresholds ensuring operational efficiency of scenarios, as well as the quality of generated alerts.

KPI reporting

• Data recovery; Data consistency check (consistency of figures, monitoring of threshold variations, etc.), iterative work with the poles.
• Regular dashboard production and data analysis; Writing comments and drawing conclusions.

Operational Committee & Annual review of scenarios

• Production/Analysis of KPIs over the period; Preparation of the Operational Committee support draft.