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Panel: Learnings Along the Data Science Product Lifecycle From a Big Corporate

04 Jun 2025
AI & Data Science
AI for Business MLOps
Are you trying to build a data science solution in-house using agile ways of working but have questions about how to get started and what to consider along the way? In this panel, we will discuss experiences and best practices from across the industry.
 
The panel discussion will shine a light on the team, culture, and tools needed to get development of a data science product started. Along the panel discussion, we will explore valuable lessons about prioritizing research tasks vs. other activities. The session will also outline the participants’ learnings on what to do to satisfy both users and stakeholders, adopting software development best practices to monitor quality and providing a resilient product as the solution evolves.
 
After this session, you will have an idea on how to start and what to expect on the journey of building in-house data science products.
 
Chairperson
Florian Roscheck, Senior Data Scientist - Henkel
Speakers
Franziska Zerwas, Data & AI Strategist - EnBW (Energie Baden-Württemberg AG)
Martin Jänicke, Head of AI Sync - ZEISS Group
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