Data Science Manager (f/m/d): SAP Foundation Model for structured data

at  SAP

WE HELP THE WORLD RUN BETTER

At SAP, we enable you to bring out your best. Our company culture is focused on collaboration and a shared passion to help the world run better. How? We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and is aligned to our purpose-driven and future-focused work. We offer a highly collaborative, caring team environment with a strong focus on learning and development, recognition for your individual contributions, and a variety of benefit options for you to choose from.

Summary:
At SAP, we amplify the strength of AI technology, fusing it with our robust industry-focused data and profound process knowledge. Our vision is to infuse every SAP application with sophisticated AI capabilities, revolutionizing the way businesses operate. Large Language Models (LLMs) hold immense potential to change the way we work and develop products. They are reshaping the landscape of Machine Learning across various domains. However, their limited ability to leverage tabular data leaves a considerable share of enterprise data untapped. It is SAP’s mission to overcome this challenge within the realm of Business AI. Our goal is to adapt Foundation Models to SAP data, enabling our clients to solve their business processes more effectively.

The Role:

• Unique opportunity to build, steer, manage and mentor a team of highly-skilled Applied AI Scientists, and Data Engineers in our Business AI hub in Berlin. Drive the development of the SAP Foundation Model for structured data embedded in a variety of business applications.
• Be accountable for the success, quality, and delivery of mMachine lLearning components.
• Collaborate with cross-functional teams including product management and design to define product requirements and ensure the timely delivery of high-quality software products.
• Foster a culture of innovation, continuous improvement, and excellence in software development.
• Act as a problem solver to address organizational and process challenges, leveraging technical expertise to bridge gaps, streamline operations, and facilitate smooth execution of partnership initiatives.
• Maintain up-to-date knowledge of AI and dData eEngineering trends and apply this expertise to improve team performance and product quality.
• Contribute to thought leadership in a revolutionary new data modality for Foundation Models and Generative AI.