This will include both projects where you will create new techniques to detect model failure as well as projects where you will validate and monitor models to determine whether an existing algorithm works as expected.

Will also be positively evaluated experience in development and/or validation of stochastic models for insurance companies (Solvency II framework), credit risk models (i.e. PD and LGD estimations for mortgage and loan portfolios) or financial risk models (i.e. non maturing deposits, pricing, pre-payment, satellite models).

As a validation expert you will interact intensively with the model development team, both providing invaluable input related to improving existing models. As a consequence you will be actively contributing to the overall model risk posture of the bank.

Must have:

• At least 3 years of hands-on experience with analytics / ML development
• Proficiency in Python as well as in the main analytics libraries (Keras, Tensorflow, scikit learn)
• Fluency in English
• Excellent verbal, written and presentation skills

Plus:

• Master or PhD in a quantitative field (data science, mathematics, physics,)
• Experience in quantitative software development
• Experience in model validation and/or quantitative finance
• Familiarity with pyspark, spark ML/MLlib
• Positive and creative mindset
• Pragmatic & client focussed