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**AML Detection Data Scientist with French** - **Role:** Data Scientist with focus on Anti Money Laundering (AML) scenarios calibration. - **Responsibilities:** Calibrate and optimize financial crime compliance scenarios, analyze generated alerts, perform ad-hoc studies, and ensure pertinence of alerts. - **Key Skills:** Proficiency in SAS, SQL, Python, R; strong statistical analysis and data analysis skills; knowledge of Power Bi, Tableau, or other BI tools; ability to work with logical propositions and operators. - **Required Experience:** At least 2 years in statistics, risk modeling, risk scoring, or AML calibration. - **Education:** Master's degree in Economic Cybernetics, Statistics, Computer Science, Banking, or Computer Science fields. - **Languages:** B2 English, good level of French. - **Other Requirements:** Knowledge of Anti Money Laundering, strong motivation to evolve in the field; good interpersonal skills, responsiveness, and adaptability; efficient, team-oriented, and autonomous with strong organizational skills. - **Why Join Us:** Flexible workplace, constant learning opportunities, dynamic culture, talented people, diverse businesses, competitive compensation, and wide range of benefits.
- Compensation
- Not specified
- City
- Not specified
- Country
- Romania
Currency: Not specified
Full Job Description
AML Detection Data Scientist with French
Responsibilities
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 Groups 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 Groups 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.
Profile required
Good knowledge of SAS, SQL, Python, R;
Statistical Analysis;
Data analysis;
Power Bi, Tableau or other Business Intelligence tool;
Analytical thinking and ability to work with logical propositions and operators;
English written and spoken level B2, good level of French would be a plus;
Knowledge related to Anti Money Laundering, financial crime detection or strong motivation to
evolving in this field is required;
Good interpersonal skills, responsiveness, and ability to communicate with the central structure
located in another country, sense of service, flexibility;
Efficiency, team spirit and ability to evolve in a fast and demanding work environment;
Autonomy and sense of organization (management of priorities and deadlines);
Graduate in Economic Cybernetics, Statistics and Computer Science, Banking or Computer
Science fields (Master or without);
+2 years of relevant experience in statistics, risk modelling, risk scoring, AML calibration.
Why join us
Here, you will find a flexible workplace and culture, autonomy, constant learning opportunities, dynamism, and talented people, making this experience a real career accelerator. You will also discover all the diversity of our businesses, in a sector that is constantly evolving and innovating.
Plus, you will enjoy all our benefits:
- competitive compensation & remuneration, including annual performance bonus;
- preventive healthcare plan, and group health & life insurance;
- wide range of flexible benefits within a monthly budget;
- office perks, wellbeing and mental health programs;
- various social benefits and bonuses for personal or family events;
- 9-to-5 workday & flexible (hybrid) work environment;
- additional paid and unpaid time off, including Sabbatical leave;
- learning and growth opportunities based on individual development and career plans;
- unlimited access to various eLearning resources.
Business insight
We are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious.
Whether youre joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating and taking action are part of our DNA.
If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us!
Still hesitating?
You should know that our employees can dedicate several days per year to solidarity actions during their working hours, including sponsoring people struggling with their orientation or professional integration, participating in the financial education of young apprentices, and sharing their skills with charities. There are many ways to get involved.
Diversity and Inclusion
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