Focus: Development and implementation of machine and deep learning projects in the areas of time series forecasting, tabular machine learning and causal inference.

• You will support and implement end-to-end machine learning projects for our customers, focusing on time series and forecasting use cases such as demand forecasting, pricing, anomaly detection, and predictive maintenance.
• You design, implement, validate, and deploy machine learning models based on tabular and time series data, ranging from classical statistical methods to modern machine learning and deep learning approaches.
• You use statistical and causal thinking to solve complex business problems and employ methods such as controlled experiments, uncertainty quantification, and decision optimization.
• You will support the development of robust, scalable, and maintainable ML pipelines and contribute to the deployment of models in production environments on modern cloud infrastructures such as Azure, AWS, or GCP.
• You work regularly with stakeholders and customer representatives and ensure close coordination within the project.
• You will work with experienced consultants, data scientists and engineers across various industries and use cases, continuously developing your technical and consulting skills.
• Depending on your experience, you will gradually take on responsibility for individual work packages, contribute to proposals, and support the further development of internal best practices in the area of ​​forecasting and applied machine learning.
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