Senior Data Scientist, HCM AI Autonomy Suite

SAP SE; Palo Alto (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

SAP SE is seeking a seasoned Data and Applied Scientist to build the semantic and contextual foundation for SAP's AI. You will create enterprise ontologies, integrate data from SAP and external sources, and develop RAG pipelines and knowledge grounding that power SAP's AI agents in production.

You will partner with product, engineering, and customer-facing teams to translate business challenges into concrete AI solutions, leveraging Databricks, SAP Datasphere, and cloud platforms across multiple

Qualifications

• 8+ years of experience in knowledge engineering, semantic data systems, applied AI, or data science.
• Master's or PhD in CS, applied mathematics, statistics, or engineering.
• Hands-on experience designing ontologies and semantic models; proficiency in graph query languages.
• Experience with GenAI, RAG, embeddings, vector databases, and enterprise knowledge grounding.
• Strong Python and SQL skills with ML libraries; production-grade development.

Responsibilities

• Design and maintain enterprise ontologies and semantic models across data landscapes.
• Build AI capabilities including RAG pipelines, embeddings, and vector databases.
• Develop generative AI solutions grounded in enterprise data and knowledge graphs.
• Leverage cloud platforms to support scalable AI workflows (Databricks, SAP Datasphere, AWS/Azure/GCP).
• Collaborate with product and engineering teams to translate business challenges into AI solutions from concept to deployment.

Skills

Knowledge engineering

Semantic data systems

Applied AI

Data science

Education

Master's degree in Computer Science or related quantitative field

Tools

Databricks

SAP Datasphere

HANA Cloud

Job description

SAP SE is seeking a seasoned Data and Applied Scientist to build the semantic and contextual foundation for SAP's AI. You will create enterprise ontologies, integrate data from SAP and external sources, and develop RAG pipelines and knowledge grounding that power SAP's AI agents in production.

You will partner with product, engineering, and customer-facing teams to translate business challenges into concrete AI solutions, leveraging Databricks, SAP Datasphere, and cloud platforms across multiple