Freelancer profile translated to English.

Description

Analytics Engineer / Data Engineerspecializing in **credit risk, fraud, and regulatory data**, I support banking and finance teams in structuring and validating their data.

I work on projects with high business and regulatory stakes, ensuring the implementation of robust data pipelines, analytical data modeling, and the necessary quality controls for compliance and decision-making.

I manage deliverables such as:

Industrialized and documented data pipelines
Reliable and exploitable data models
Data controls and acceptance testing
Dashboards for steering needs

My approach is focused on quality, traceability, and understanding business needs to deliver truly actionable data solutions.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

CACIB
Data Engineer
BANKING AND INSURANCE
December 2024 - April 2025 (4 months)
Montrouge, France
Involved in implementing reliable and traceable data pipelines for Basel IV regulatory reporting, in a context of high compliance stakes.

Responsibilities and achievements:
• Development of data pipelines in Python and Spark to feed regulatory reports
• Implementation of validation tests to ensure data robustness, consistency, and quality
• Documentation of processes to facilitate their use and deployment
Python Spark SQL Minio
LCL
Data Analyst
BANKING AND INSURANCE
September 2021 - July 2024 (2 years and 10 months)
Villejuif, France
Worked on fraud detection and prevention issues, from data preparation to real-time operational monitoring.

Responsibilities and achievements:

• Cleaning and preparation of data in Python to ensure a high level of quality and reliability for fraud analysis
• Definition and implementation of fraud detection rules adapted to different payment methods (especially checks)
• Extraction and manipulation of data in SQL on Teradata to feed fraud analysis and models
• Design and automation of fraud monitoring dashboards on Qlik Sense, enabling effective operational steering
• Development of ETL pipelines under Dataiku: data extraction from Teradata (SQL)
- business processing and enrichment in Python - automation of workflows with alerts, notifications, and reporting for business teams
• Implementation of data quality indicators (missing value rates, date consistency, contract ID duplicate detection, etc.) to ensure reliable analysis and decisions
Python SQL Dataiku Teradata Qlik