Senior Enterprise AI Scientist & Data Architect

SAP SE; Iowa; Híbrido; USD 274.000 - 609.000; Tempo integral

Resumo da vaga

SAP SE is seeking an experienced Data and Applied Science professional to build the semantic and contextual foundation of SAP's AI. You will work on AI capabilities using enterprise data, knowledge graphs, and business process intelligence, partnering with product and engineering teams to deliver scalable, production-ready solutions.

You will design ontologies, work with cloud platforms, and translate business challenges into concrete AI use cases, ensuring measurable business outcomes across

Qualificações

• Master’s degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields.
• 10+ years of experience in machine learning, deep learning, generative AI, and LLMs with hands-on model development and evaluation.
• Strong Python and SQL skills with production‑grade development.
• Experience deploying ML/AI solutions in production and working with big data platforms such as Databricks.

Responsabilidades

• Translate business challenges into AI use cases and measurable outcomes.
• Develop end-to-end ML/AI solutions from data preprocessing to deployment and lifecycle support.
• Collaborate with product, engineering, and customer-facing teams to ensure scalable, production-ready solutions.

Conhecimentos

Python

SQL

ML frameworks

Communication

Formação

Master’s degree or PhD in Computer Science or related quantitative field

Ferramentas

Databricks

SAP Datasphere

HANA Cloud

Descrição da vaga

SAP SE is seeking an experienced Data and Applied Science professional to build the semantic and contextual foundation of SAP's AI. You will work on AI capabilities using enterprise data, knowledge graphs, and business process intelligence, partnering with product and engineering teams to deliver scalable, production-ready solutions.

You will design ontologies, work with cloud platforms, and translate business challenges into concrete AI use cases, ensuring measurable business outcomes across