The team applies advanced analytics—including machine learning, quantitative algorithms, and data mining techniques— to obtain business insights and solve problems. We are actively involved throughout the entire lifecycle, from initial design to final implementation. Our stakeholders span all areas of the bank, including business, risk, retail, and corporate banking.

Our scope of work includes:

Building and maintaining a robust codebase that supports the creation of ML modelsTraining, deploying, and monitoring machine learning models tailored to various business needs.Conducting ad hoc data analysesDeveloping dashboards and tools to enhance data accessibility and support a more data-driven organization.

The employee will focus on developing a deep learning model for the mortgage portfolio. Specifically, they will evaluate different approaches and compare them with the model currently in production.

For this purpose, we are looking for students interested in writing their thesis on this topic.

Experiences:

Practical experience (at least 2+ years) with programming language such as PythonFamiliarity with machine learning libraries and frameworks (e.g. scikit-learn...)Knowledge of Object-Oriented Programming and Git workflows

Nice to Have:

Personal public projects on GitHub/Azure or similarExperience with Keras/TensorFlow for deep learning models.Experience with CI/CD pipelines and DevOps practices

Skills:

Demonstrated solid data handling skills.Fluent written and spoken EnglishStrong verbal and written communication skills

Personal Characteristics:

Self-driven with the ability to figure out solutions by him or herselfAbility to work collaboratively in a team environment.Must possess an energetic, self-motivated work ethic.Effectively communicate with many levels.Proven to perform under pressure.High ethical standards, honesty, integrity.