Your area of work:
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 ensuring the robustness, accuracy, and compliance of the risk models used at Clearstream. This is your chance to gain hands-on experience in a high-stakes environment, working with professionals who validate cutting-edge financial models.
Your responsibilities:
- Assist in validating risk models used for operational risk, credit risk, market risk, and liquidity risk management.
- Help perform statistical analyses and backtesting to assess model performance.
- Assist reviewing model assumptions, methodologies, and limitations.
- Help develop and run stress-testing frameworks to evaluate model robustness under extreme scenarios.
- Research innovative approaches to enhance model accuracy and validation processes.
- Support the team with document findings and prepare validation reports in alignment with regulatory requirements (e.g., CSDR, MaRisk).
Your profile:
- You must be enrolled in a Master’s degree in in a quantitative field such as Finance, Mathematics, Statistics, Computer Science, Economics, or related disciplines, and can provide an internship agreement, OR have graduated with a Bachelor's degree or similar for no more than 6 months
- Familiarity with statistical analysis, probability theory, predictive modeling, data science techniques, time series analysis, clustering, etc.
- Basic understanding of financial products (e.g., fixed income) and risk management concepts.
- Excellent problem-solving abilities with a keen eye for details.
- Strong ability to interpret and critically analyze data.
- Effective communication and writing skills.
- Ability to work both independently and collaboratively in a team.
- Fluent in English (spoken and written).
- Strong programming skills in Python.
- We strongly recommend the upload of university grade reports/transcripts, certificates and reference letters.