You will design, build, and deploy machine learning and statistical models for fraud detection, transaction monitoring, loan risk assessment, customer risk scoring, and sales and lead generation. You will operate experimentation and evaluation frameworks, analyse data, engineer features, collaborate on requirements, and document models and results clearly.
Responsibilities
- Design, build, and deploy machine learning and statistical models across fraud detection, transaction monitoring, loan risk assessment, customer risk scoring, and sales and lead generation
- Build and operate experimentation and evaluation frameworks using tools such as MLflow and Metaflow
- Analyse data and engineer features to improve model performance
- Partner with data engineers, analysts, and business stakeholders to define requirements and turn insights into decisions
- Document models, methodologies, and results clearly
- Apply current machine learning and GenAI advances
Requirements
- Develop and deploy machine learning models in a production environment
- Use Python and machine learning libraries such as scikit-learn, TensorFlow, and PyTorch
- Use cloud-based machine learning platforms such as AWS SageMaker or Kubeflow
- Apply machine learning, statistical modeling, and data analysis techniques
- Communicate technical concepts as business insights
- Provide criminal-record information or consent to its collection where required by local regulations
- Not be registered in RKI
Benefits
- State-of-the-art computer, monitor, mouse, and keyboard
- Pension
- Health insurance
- Enhanced parental leave