Your role at Zeiss Digital Partners:
- Perform in-depth data analysis in a variety of areas (e.g. production, supply chain management, intralogistics, customer 360°, web analytics, etc.)
- Supporting our business segments with specific evaluations as well as analyzing and preparing data, data sources and interfaces of different (structured and unstructured) formats.
- Connect data from different data sources (esp. ERP or CRM systems), define user-oriented measurement values (KPIs) and provide valuable insights through suitable visualizations.
- Requirements Engineering: Understanding functional requirements of the client for the process to be optimized and translating them into user stories.
- Assess technical feasibility - develop prototypes and sustainable solutions on your own and/or in collaboration with Data Engineers or Data Scientists.
- Identify potential solution scenarios, systems and data sources to support prototype and product realization.
- Identify conflicts between business and IT requirements and propose solution options.
- Recognizing and managing risks.
- Analysis and interpretation of results.
- Creation and visualization of reports and recommendations for decision making.
- Implementation of your ideas and solutions based on the latest technologies, while striving to standardize the BI processes of our customers.
- Direct contact person for your customers for the entire project cycle, working closely with the business and IT departments and cooperate within a team of experts.
- Help establish a data-driven culture at ZEISS.
- With your extensive knowledge and experience, you will also contribute to further improving our development processes and help shape best practices within the team.
Your profile:
- Degree in Computer Science, Finance, Engineering, or Natural Sciences.
- 3+ years in Data Analysis, Data Engineering, or Data Visualization.
- Strong skills in Python (git, Azure DevOps), SQL/NoSQL, and cloud technologies (Azure, Databricks, PySpark).
- Experience with BI/visualization tools (Power BI, Plotly/Dash, etc.).
- Understanding of statistics, machine learning basics, and business context.
- Stakeholder management experience in analytics projects.
- Creative, analytical, detail-oriented, proactive, and self-driven.
- Excellent communication and presentation skills.
- Fluent in English; German is a plus.
The following skills are considered as a plus:
- GenAI interface integration (Azure/AWS) and LLM frameworks like LangChain.
- R, AutoML, NLP/AI packages, and Retrieval-Augmented Generation (RAG).
- Knowledge of graph databases and agentic workflows.
What we offer:
Our employees are the innovative backbone and driving force of our company. That is why you are our focus.
- Technology stack: Modern and cutting-edge technology stack with opportunities to experiment and innovate within a high-tech group
- Flexible work options: 40-60% hybrid work option to provide flexibility and work-life balance
- Additional benefits: Annual flexible benefits that include cafeteria options, private health plans, and annual reward
- Extra option: Company parking space in the underground garage of the office building can be reserved
- Contribution: Opportunity to directly contribute to the development of innovative products through software delivery
- Supportive work environment: working in a team composed of excellent teammates and a supportive lead who collaborate to guide and support professional development from day one
At ZEISS we encourage creative thinking and innovation. We work in dynamic and interdisciplinary teams and offer individual development perspectives and flexibility in organizing your work. We care about our employees and take responsibility for improving society and preserving our environment. These core values have shaped our corporate culture at ZEISS for over 175 years.
Join our inclusive and diverse #teamZEISS and enable the digital future for ZEISS and our synergy clients
The application process takes less than 10 minutes, seize the moment.
Your ZEISS Recruiting Team:
Bartha Györgyi, Fedor Fanni, Meláth Laura, Sturcz Noémi, Sztaskó Daniella, Wenner Lili