Ingénieur Machine Learning / Développeur Python F/H

Job Title: Python Developer – Banking Sector

We are seeking an experienced Python Developer with a strong background in the banking or financial services domain . The ideal candidate will have hands-on experience building and maintaining data pipelines, feature engineering workflows, and data cleansing solutions to support analytics, predictive modeling, and banking operations.

This role is critical in ensuring high-quality, scalable, and efficient data solutions that drive business insights and operational decision-making.

Data Engineering & Processing

Design, develop, and maintain scalable Python-based data pipelines to handle large volumes of banking data, including transactions, customer information, and financial records.
Implement efficient ETL (Extract, Transform, Load) processes to integrate data from multiple banking systems and external sources.
Optimize data workflows for performance, reliability, and scalability , supporting both real-time and batch processing.
Collaborate with data scientists and analysts to develop feature engineering solutions for credit risk, fraud detection, and customer analytics.
Transform raw banking data into meaningful features to enhance predictive model performance .
Create and maintain feature stores and reusable pipelines to support ML initiatives.
Data Quality & Cleansing

Implement data validation frameworks and cleansing routines to ensure accuracy, consistency, and completeness.
Identify and resolve data quality issues, including missing values, duplicates, outliers, and inconsistencies.
Develop automated data quality monitoring and alerting systems.
Technical Development

Write clean, efficient, and well-documented Python code following industry best practices.
Develop and maintain APIs and microservices for data access and integration.
Implement unit tests , integration tests, and participate in code reviews to ensure high-quality deliverables.
Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field (or equivalent practical experience).
Minimum 5 years of professional Python development experience .
Proven experience in banking, financial services, or fintech , with understanding of banking products, processes, and regulations.
Technical Skills

Expert-level Python programming with libraries such as pandas, NumPy .
Hands-on experience in feature engineering (encoding, scaling, binning, transformations, dimensionality reduction).
Expertise in data cleansing and validation methodologies.
Proficiency with SQL and relational databases (PostgreSQL, MySQL, Oracle).
Experience with version control (Git) and CI/CD pipelines .
Strong understanding of banking concepts: retail/corporate banking, payments, lending, or risk management.
Knowledge of banking data structures, transaction processing, and regulatory reporting.
Awareness of data privacy and compliance standards (e.g., Experience with ML model deployment and MLOps practices .
Familiarity with data visualization tools (Tableau, Power BI, matplotlib, seaborn, plotly).
Understanding of software design patterns and architectural principles.
Exposure to Agile/Scrum methodologies.