Data Scientist - Credit Risk Modeling

About:

• Proven experience in developing and deploying credit risk models (e.g., Application scoring, behavioural scoring).
• Solid understanding of credit risk assessment techniques, including statistical, machine learning, and traditional risk modelling approaches.
• Experience in using data science and statistical software (e.g., Python, Pyspark) for data analysis and model development.
• Strong communication skills, with the ability to present complex analytical results to non- technical stakeholders.
• Experience in model deployment practices.