Model Validation Specialist
Il y a 21 heures
Luxembourg, Prague
Deutsche Börse Group
Temps plein
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About Clearstream
Clearstream, part of the Deutsche Börse Group, is a leading global provider of post-trade services, offering settlement, custody, and collateral management solutions. Our expertise ensures stability, efficiency, and transparency in financial markets worldwide.
The Model Validation Team plays a critical role in safeguarding the robustness, accuracy, and regulatory compliance of the risk models used across Clearstream. As a full-time Model Validation Specialist, you will contribute directly to the integrity of our risk framework and help ensure that our models meet high quantitative and regulatory standards.
Your
Responsibilities:
• Independently validate risk models used for operational, credit, market, and liquidity risk management.
• Conduct advanced statistical analyses, benchmarking, and backtesting to assess model performance.
• Review and challenge model assumptions, methodologies, conceptual soundness, and implementation.
• Design and execute stress-testing and scenario analysis to assess model behavior under extreme conditions.
• Propose enhancements to improve model robustness, accuracy, and regulatory compliance.
• Collaborate closely with model developers, risk managers, and stakeholders across the organization.
• Draft comprehensive validation reports aligned with internal standards and regulatory frameworks (e.g., CSDR, MaRisk, ECB guidelines).
• Support internal and external audit processes and regulatory inquiries.
Your Profile
We are looking for an analytical and proactive professional with the following
qualifications:
• Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Statistics, Physics, Computer Science, Economics, or related discipline.
• Minimum of 2–3 years of relevant professional experience.
• Strong programming skills in Python; experience with libraries such as NumPy, pandas, SciPy, or scikit-learn is a plus.
• Solid understanding of statistical analysis, probability theory, time series analysis, predictive modeling, quantitative finance, and machine learning methods.
• Knowledge of financial products (e.g., fixed income, derivatives) and risk management concepts.
• Experience with model development, validation, or quantitative risk analysis is a strong advantage.
• Excellent quantitative problem-solving abilities and a rigorous, detail-oriented working style.
• Ability to interpret, explain, and critically assess complex data and models.
• Strong communication skills, with the ability to articulate complex quantitative concepts to diverse stakeholders.
• Ability to manage multiple tasks, work independently, and collaborate effectively within a team environment.
• Proactive mindset with a willingness to challenge assumptions and propose improvements.
• Former management experience is an advantage.
• Fluent in English (spoken and written); German language skills are an advantage.
Responsibilities:
• Independently validate risk models used for operational, credit, market, and liquidity risk management.
• Conduct advanced statistical analyses, benchmarking, and backtesting to assess model performance.
• Review and challenge model assumptions, methodologies, conceptual soundness, and implementation.
• Design and execute stress-testing and scenario analysis to assess model behavior under extreme conditions.
• Propose enhancements to improve model robustness, accuracy, and regulatory compliance.
• Collaborate closely with model developers, risk managers, and stakeholders across the organization.
• Draft comprehensive validation reports aligned with internal standards and regulatory frameworks (e.g., CSDR, MaRisk, ECB guidelines).
• Support internal and external audit processes and regulatory inquiries.
Your Profile
We are looking for an analytical and proactive professional with the following
qualifications:
• Master’s degree or PhD in a quantitative field such as Finance, Mathematics, Statistics, Physics, Computer Science, Economics, or related discipline.
• Minimum of 2–3 years of relevant professional experience.
• Strong programming skills in Python; experience with libraries such as NumPy, pandas, SciPy, or scikit-learn is a plus.
• Solid understanding of statistical analysis, probability theory, time series analysis, predictive modeling, quantitative finance, and machine learning methods.
• Knowledge of financial products (e.g., fixed income, derivatives) and risk management concepts.
• Experience with model development, validation, or quantitative risk analysis is a strong advantage.
• Excellent quantitative problem-solving abilities and a rigorous, detail-oriented working style.
• Ability to interpret, explain, and critically assess complex data and models.
• Strong communication skills, with the ability to articulate complex quantitative concepts to diverse stakeholders.
• Ability to manage multiple tasks, work independently, and collaborate effectively within a team environment.
• Proactive mindset with a willingness to challenge assumptions and propose improvements.
• Former management experience is an advantage.
• Fluent in English (spoken and written); German language skills are an advantage.