Barclays is a global organization that specializes in quantitative analytics. The Quantitative Analytics (QA) team, led by Olaf Springer, develops, tests, implements, and supports quantitative models for valuation and risk management across various areas. The QA Market Risk team, which is part of the QA Trading Cross-Product functional area, is responsible for developing and supporting risk, capital, and RWA models for the Barclays investment bank. They follow industry and regulatory standards to ensure accurate risk management. The team is distributed across London, New York, and Prague and takes pride in their collaborative work.

In this role you can expect to have the responsibilities:

• Apply cutting-edge machine learning and artificial intelligence methodologies to enhance market and counterparty credit risk monitoring and management.
• Develop computational methods and mathematical and statistical models for risk management applications.
• Research, formulate, and implement quantitative models and solutions to optimize pricing and risk management of financial products across various asset classes.
• Perform computations and assess numerical implementations of analytical modules, models, and methodologies using mathematical and statistical analysis.
• Validate, formulate, and test quantitative pricing models to ensure adequacy.
• Implement and maintain analytics models and applications using Python.
• Build optimization tools using Python for counterparty risk management.
• Define data requirements and perform theoretical modeling, empirical testing, historical backtesting, and statistical analysis of large datasets.

This role requires you to have:

• Machine Learning
• Python
• Mathematical and Statistical Modeling
• Risk Management
• Quantitative Analysis
• Numerical Analysis