They first asked some questions around the data analysis I had to present at the beginning of the interview (that I had 6 days to prepare the presentation). Then they went to competency based questions, mainly around people management and project/time management. Lastly the focus was around technical knowledge relevant to the role (types of models, regulations that I know of that impact the credit risk space, their impact).
Your favorite courses at school.
Tell me about yourself.
Describe your experience working with ML models. What models have you used before?
Why quit current job, why sentilink?
Questions classiques sur les calls, puts, le modèle de Black & Scholes. Puis questions plus techniques de maths sur le calcul stochastique (Itô, Girsanov), les séries temporelles (définition et stationnarité) , les différentes méthodes de Monte-Carlo et leurs efficacités. Ensuite des questions de programmation. Pour finir, quelques questions de motivation (en français puis en anglais).
Why Deloitte? Why Financial Risk Management? What is your biggest weakness? Where do you see yourself in five years? What is your biggest accomplishment in life?
How many types of PD models?
What is XG boost that you've mentioned here in your ML project description
Here are the numbers, calculate this
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