Your Role

In cross-functional teams, you will drive & manage projects in the field of Machine Learning (ML) and Data Science with a focus on timeseries forecasting and financial forecasting. In this role, you will support the preparation and execution of Data Science / ML projects: from setting the scope to roadmap-planning, to execution in an agile manner, to lessons learned that can be integrated into new projects. As part of a vivid team, you will be in contact with users from different ZEISS departments, assess and plan Data Science- and ML-related tasks and report outcomes and results. With your organizational and project management skills, you will enable our experts to focus on technical, high-quality solutions. You will be at the interface between our technical experts and different ZEISS departments to create great Software products. You will be an advocate of the work of our Data & Analytics team.

Your Profile

  • An excellent University degree (Ph.D. is a plus) in Natural Science, Mathematics, Computer Science, Engineering, or equivalent

  • At least 3 years of professional experience in project management in Machine Learning / Data Science, focused on timeseries data and Financial Forecasting

  • Professional experience as a Product Owner

  • The ability to understand the technical architecture of ML / Data Science solutions and State of the Art Web Apps

  • Experiences with best practices in timeseries modeling, forecasting model development, deployment, and operation

  • A good understanding of the power of standardization at the core and innovative flexibility at the shell

  • Experience in stakeholder management

  • The ability to understand customer needs and solve real-world problems

  • Strong communication, presentation, and project management skills

  • Basic knowledge of corporate data governance best practices (e.g., working with confidential data)

  • Fluent German and English language skills

Your ZEISS Recruiting Team:

Markus Repp

Location

München

Job Overview
Job Posted:
3 months ago
Job Expires:
Job Type
Full Time

Share This Job: