Intern - Clearstream Model Validation (f/m/d)

Deutsche Boerse

LU · Posted Oct 16

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At a glance

Location: Luxembourg
Work type: Onsite

Internship in Clearstream Model Validation at Deutsche Börse in Luxembourg, focusing on validating risk models across operational, credit, market, and liquidity risk; involves statistical analyses, backtesting, stress testing, and regulatory reporting support.

What they are looking for

PythonStatisticsTime_seriesData_sciencePredictive_modeling

Location: Luxembourg, LU

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.