Design, develop, and maintain quantitative methodologies that incorporate climate risk into provisioning, stress testing, and economic capital frameworks
Apply statistical, econometric, and machine learning techniques to estimate financial impacts derived from climate scenarios
Prepare detailed Model Development Guidelines and backtest Guidelines
Monitor the resolution of the different model recommendations
Participate in international Climate Risk related working groups
Be up to date in the most recent Climate risk related regulation
Work closely with credit risk, sustainability, and regulatory teams to ensure the effective integration of climate risk

Degree in Physics, Mathematics, Engineering, or another quantitative discipline
Master’s in Machine Learning, Data Science, or similar is required
FRM/SCR/RAI certifications are valuable
At least 7 years of experience in quantitative model development or analytics, preferably within the banking or financial sector
3 years of experience developing Climate Risk related models
Proficiency in Python/SQL/PySpark and data management tools AWS (Athena/Sagemaker/Engines)
Knowledge of credit risk modeling (PD, LGD, EAD) and/or stress testing
Experience applying machine learning techniques to risk or climate modeling
Knowledge of climate scenario frameworks (NGFS, IPCC) and regulatory guidance (EBA, ECB) is a plus
Excellent communication skills in Spanish and fluent in English (B2)

Data Scientist – Control Manager/Senior Manager

Key skills