Your Role

In cross-functional teams, you will drive & manage projects in the field of Machine Learning (ML) and Data Science. 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 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 Computer Science, Engineering, Mathematics, Natural Science, or equivalent

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

  • Experiences in Feature Engineering, Unsupervised & Supervised Learning, model deployment and operation in the cloud

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

  • At least 3 years of professional experience in Project Management of Machine Learning & Data Science solutions

  • Professional experience as a Product Owner

  • Experience in stakeholder management

  • Experience with cloud-deployed ML solutions for customers

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

  • Strong communication, presentation, and Project Management skills

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

  • Fluent English and German language skills

Your ZEISS Recruiting Team:

Markus Repp

Location

München

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

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