The impact You will create:

• Develop complex data products that are integrated into our business processes and generate added business value

• Assess and process relevant data sources. Evaluate, implement and optimize suitable algorithms

• Utilize and build on of state-of-the-art data science techniques, e.g., classic machine learning or deep neural networks

• Integrate models into productive software and industrialize them (MLOps, DevOps)

• Work in interdisciplinary, agile project teams

• Present results to stakeholders

Experience and skills You will need:

• Completed university degree in data science, mathematics, statistics, computer science, physics, or a related field

• Ideally several years of professional experience as a machine learning engineer or data scientist

• Practical experience with forecasting and pricing use cases and common models (gradient boosting machine, neural networks, (S)ARIMA, Prophet)

• Very good knowledge in the application of machine learning, optimization and data mining methods (e.g., with Python, Spark)

• Ideally experience with distributed machine learning frameworks and model lifecycle management (e.g., MLFlow)

• Practical knowledge of development with Python and knowledge of the software development cycle (e.g., CI/CD, DevOps, testing)

• Knowledge of big data (SQL, Spark/Databricks) and cloud technologies (Azure, GCP)

• Experience with agile software development methods

• Ability to understand complex issues and scenarios, analyze them in detail and present the findings to a non-technical audience in an understandable way

• Very good knowledge of English (at least C1 level)