Description

You will develop and maintain risk models for regulatory stress testing and company risk management.

This role is on-site.

Responsibilities

• Develop risk models in Python or R for regulatory stress testing and company risk management.
• Design execution workflows to forecast Balance Sheet, Fee Revenues, Macroeconomic Factors, and Expenses, calculating risk metrics under stress scenarios.
• Coordinate with functional teams to implement, test, and document financial models.
• Develop processes and tools to monitor model performance, applying statistical tests to validate results.
• Apply data mining, data modelling, and ML techniques to enhance model performance on large financial datasets.

Required Skills

• 7+ years of relevant work experience based on education level.
• Master/MBA/PhD in a quantitative field (computer science, financial engineering, mathematics, data science, or engineering).
• Expertise using Python and R, alongside proficiency in SQL and Pandas for data manipulation.
• Understanding of the design, development, and implementation of mathematical, financial risk, and ML models.
• Knowledge of advanced statistical techniques (regression, time series analysis, statistical tests).
• Experience with programming languages including Java, C++, Matlab, and Jupyterhub.
• Strong written and verbal communication skills for cross-team coordination.

Key Skills

Education

Master/MBA/PhD's Degree