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.