Data Scientist – Credit Risk and Fraud

This is a remote position.

• Design and maintain credit risk and fraud detection models
  
• Perform feature engineering on large structured financial datasets
  
• Train, validate, and optimise machine learning models for production use
  
• Monitor model performance and implement continuous improvements
  
• Collaborate with ML engineers on deployment, tracking, and lifecycle management
  
• Integrate model outputs into LangChain and LangGraph orchestration pipelines
  
• Ensure model explainability, robustness, and regulatory compliance
  
• Support documentation and governance requirements in a regulated environment
  

Requirements

• Strong hands-on experience in Data Science and applied Machine Learning
  
• Proficiency in Python and common data science libraries (Pandas, NumPy, scikit-learn)
  
• Experience with gradient boosting frameworks such as XGBoost or LightGBM
  
• Strong SQL skills and experience working with large datasets
  
• Experience with PySpark or distributed data processing
  
• Experience with MLflow for experiment tracking and model management
  
• Understanding of production model lifecycle and monitoring practices
  
• Ability to work in regulated or risk-sensitive environments
  
• Fluent English for professional collaboration
  
  

• Experience in credit risk, fraud detection, or financial services
  
• Exposure to LangChain and LangGraph for orchestration of analytical outputs
  
• Experience integrating ML models into real-time decision systems
  
• Understanding of model interpretability and explainability frameworks
  

Benefits

• Solid, competitive salary
  
• Work in a multinational environment on international projects
  
• Comprehensive healthcare
  
• Long-term B2B contract with a stable project pipeline
  
• Remote work model