Senior Quantitative Risk Analyst – Financial Services

Our client is a leader in financial services dedicated to delivering cutting-edge solutions for collateral management.

• At least 5 years of experience in quantitative risk modeling or related fields.
• Strong expertise in Python (Pandas, NumPy, scikit-learn).
• Proven experience with SQL and handling large datasets.
• Deep understanding of statistical methods, probability, and time series analysis.
• Practical knowledge of collateral management, including building and validating models.
• Experience in finance, risk, trading, portfolio management, or treasury is a plus.

Nice to have:

• Experience with machine learning frameworks like TensorFlow or PyTorch.
• Familiarity with Bloomberg and CALYPSO platforms.

• Lead the design, build, and validation of quantitative models, including predictive and risk models such as VaR.
• Analyze market data and time series to inform model calibration and backtesting procedures.
• Develop and maintain robust Python scripts utilizing Pandas, NumPy, and scikit-learn for data processing and modeling.
• Optimize models through calibration and perform rigorous backtests to ensure quality and accuracy.
• Manage large datasets using SQL, ensuring data integrity and efficient data handling.
• Collaborate with cross-functional teams to integrate models into operational systems.
• Contribute to the continuous improvement of collateral management processes and tools.

Only candidates with an existing legal right to work in the European Union will be considered for this role.