Data Scientist – Credit Risk Modeller

Turn complex lending and customer data into dependable predictive models, clear insight and practical recommendations. You will own meaningful parts of the model lifecycle—from data preparation and feature engineering through validation and deployment readiness—helping teams make better, more responsible credit decisions.

Profile for success

• Demonstrated experience developing credit-risk, credit-scoring or comparable predictive models within financial services.
• Evidence of personally taking analytical or modelling work from problem framing and exploration through validation and deployment readiness.
• Strong hands-on Python and SQL capability, including efficient analysis of large datasets; GCP and BigQuery experience is highly relevant.
• Experience applying statistical analysis, feature engineering, model validation and monitoring for performance, stability or drift.
• Clear examples of converting business questions into rigorous analytical frameworks and communicating findings to varied audiences.
• A relevant Bachelor's or Master's degree in mathematics, statistics, computer science, data analytics/science or a related field.