Description

You will develop and maintain risk models using Python for regulatory stress testing and internal risk management.

This role is on-site.

Responsibilities

• Design and build execution workflows to forecast Balance Sheet, Fee Revenues, and Macroeconomic Factors.
• Calculate risk metrics under stress scenarios, sensitivity, and attribution analysis.
• Apply statistical tests to validate models and develop processes to monitor model performance.
• Coordinate implementation, coding, testing, and documentation of financial models across functional teams.

Required Skills

• 3-8 years of relevant work experience.
• Proficiency in Python and R; experience with C++, Java, or Matlab is required.
• Expertise in data manipulation using SQL and Pandas.
• Understanding of designing, developing, and implementing financial risk and ML models.
• Knowledge of advanced statistical techniques (regression, time series analysis, statistical tests).
• Experience applying data mining and machine learning techniques to financial datasets.
• Familiarity with version control systems, including GitHub.

Preferred Skills

• Ability to develop presentation decks using visual analytics tools (e.g., JupyterHub/Python).

Key Skills

Education

Bachelor's or Master's degrees