Desiree Nübler

• Statistical consulting for clients and communication with internal and external stakeholders.
• Compiled, cleaned and manipulated data for proper handling.
• Modeled predictions with feature selection algorithms.
• Building knowledge graphs using LLM.
• Data Visualization for building a dashboard.
• Implementing coding standards and modularizing code base.

Tools: Python| R| Git| Hugging Face| VS Code|

Quantitative trainee program consisting of 4 stations of 3 months each.

Station 1 - Model Validation Unit:

• Validation of mathematical models (credit risk) for use in risk assessment.
• Stress testing for the European banking supervision authority.

Station 2 - Risk Systems:

• Modeling of a test portfolio for loans.
• Designing and implementing an HR chatbot "Delphi".

Station 3 - Quantitative Analytics in Markets:

• Implementation of monotone convex spline interpolation for the construction of yield curves as a component of the in-house programmed software.

Tools: R| Git| SQL| SAS EG| VS Code| C#| Git|

• Time series analysis and decomposition.
• Developing a script-based dashboard for the automated analysis and visualization of KPIs.
• Forecasting the success of advertising within an AI project group using various machine learning algorithms.

Tools: R| Python| Tableau| Git| SQL|

• Creating and optimizing of questionnaires and field documents.
• Designing a survival analysis using Cox regression and a mixed model.
• Customer management and communication.

Tools: SPSS| R|

• Coordination and evaluation of the evaluation of courses.
• Communication of the results.
• Statistical testing of the results.

Tools: SPSS|