Role overview
This is a remote position.
We are looking for a Data Scientist to join an enterprise decision intelligence platform within a global banking environment. The role focuses on credit risk and fraud prevention across multiple international markets, supporting real-time and batch decisioning in production banking systems. The platform combines large-scale structured data processing, machine learning models, and GenAI orchestration layers. It operates at significant scale under strict latency, availability, and regulatory requirements and is continuously expanded with new models, data sources, and reasoning components.
What you'll work on
- 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
What we're looking for
- 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
Tags & focus areas
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