Machine Learning Engineer AI Forecasting (m/w/d)

The Schwarz IT supports the entire digital infrastructure and all software solutions of the companies of the Schwarz Group. It is therefore responsible for selecting, providing and operating as well as further developing IT infrastructures, IT platforms and business applications. In order to optimally support the departments through IT solutions in their business processes, the Schwarz IT takes up the requirements of the departments in consultations and works together with these professional and efficient IT solutions. In the field of Artificial Intelligence Forecasting, we develop data products for the entire Black Group. We use up-to-date cloud and AI technologies to develop and operate innovative solutions for a variety of business areas, from production to the branch business to logistics. As a machine learning engineer, you work with data and software engineers on AI solutions that create real added value in a global group. Development of complex data products that are integrated into our business processes and generate entrepreneurial added value

Assessment and preparation of relevant data sources Evaluation, implementation and optimization of appropriate algorithms Targeted applications of state-of-the-art data science techniques Integration of models into productive software Industrialization of models (MLOps, DevOps) Work in interdisciplinary, agile project teams Professional leadership and guidance of team members Presentation of results from stakeholders

Completed university studies in the field of Data Science, Mathematics, Statistics, Computer Science, Physics or a subject related subject

Multiannual professional experience as a machine learning engineer or data scientist Practical experience with forecasting and pricing applications and common models (gradient boosting machine, neural networks, (S)ARIMA, Prophet) Very good knowledge of 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 Python development and software development cycle (e.g. CI/CD, DevOps, Testing) Experiences in handling big data (SQL, Spark/Databricks) and cloud technologies (GCP, Azure) Experience with methods of agile software development Ability to understand complex questions and scenarios, to analyze in detail and to present the findings to a non-technical audience in a comprehensible manner Very good knowledge of English and German (C1 level) JOBV1_EN