Senior Data Scientist - Industrial Applications (f/m/x)

Your role

You will play a crucial role in shaping the future of Data Science and actively contribute to the success of the digital transformation at ZEISS. As part of our rapidly growing Enterprise Data & Analytics organization within the Data Science team, you develop targeted data-driven solutions with a focus on Industrial Applications in our manufacturing business units. In close collaboration with colleagues from manufacturing departments, you explore complex IoT-data (e.g., measurement data, sensor signals, machine parameters), solve challenging problems and uncover potential for optimization. You will transform business needs into technical solutions, from early explorative analyses to fully functional and operational solutions. You will actively contribute to the exchange of knowledge within the team and the ZEISS machine learning community.

Your profile

1. An excellent university degree (PhD is a plus) in natural science, mathematics, computer science, engineering or similar.
2. At least 5 years of professional experience in a (industry) Data Science role or 4 years PhD/research experience + 2 years of professional experience in a (industry) Data Science role.
3. A deep understanding of data analytics and machine learning and their underlying algorithms, especially their applications for sensor time-series, IoT, digital twins and other Industry 4.0 areas.
4. Experience with manufacturing and industrial related development and processes, such as production planning, quality control, inventory management, logistics and supply chain. Knowledge of optics and photolithography processes is a plus.
5. Experiences with best practices in model development and deployment (Azure Machine Learning Service/ MLflow).
6. A background in software development (Python, git, Azure DevOps) and familiarity with agile methods.
7. The ability to understand customer needs and solve real-world problems and to prepare, communicate and discuss complex technical facts in the operational environment.
8. Pronounced results orientation and strong strategic and conceptual skills.
9. Fluent English and advanced German language skills.