Chief Data Scientist — Supply Chain AI & Semantics

SAP; Bellevue (WA); On-site; USD 283,000 - 606,000; Full time

Job summary

SAP is building an enterprise AI context engine within the Data and Applied Science team. You will translate business challenges into concrete AI designs, develop end‑to‑end ML solutions, and collaborate with product, engineering, and customer teams to deliver scalable, production‑ready outcomes.

The role emphasizes deep SAP data knowledge, semantic modeling, and cutting‑edge AI capabilities across ERP‑related domains, shaping SAP's AI future.

Qualifications

• Master's degree or PhD in Computer Science, Applied Mathematics, Statistics, Engineering, or related quantitative fields.
• 10+ years of experience to include deep expertise in machine learning, deep learning, statistical modeling, generative AI, and LLMs, with hands‑on experience developing, evaluating, and improving models using real‑world datasets — including data preprocessing, feature engineering, and experimentation — and strong analytical and mathematical modeling skills.
• 10+ years of experience in machine learning, data science, applied AI, AI research, knowledge engineering, or semantic data systems in industry, research labs, or advanced academic environments.
• Strong Python and SQL skills, including production‑grade Python development and experience with ML libraries such as PyTorch, TensorFlow, and scikit‑learn.
• Demonstrated experience of deploying, shipping, and operating AI or machine learning solutions in production environments, including production handoff and lifecycle support.
• Experience with big data infrastructure, data processing and transformation tools such as Databricks, and cloud environments such as AWS, Azure, or Google Cloud Platform.

Responsibilities

• Design and maintain enterprise ontologies and semantic models to improve interoperability, entity consistency, and business context across SAP and non‑SAP data landscapes.
• Work with cloud and data platforms to support reliable AI workflows.
• Translate ambiguous business challenges into concrete AI use cases, technical designs, and measurable outcomes.
• Design, develop, evaluate, and operationalize end‑to‑end machine learning and AI solutions from data preprocessing to deployment and lifecycle support.
• Partner with product, engineering, business, and customer‑facing teams to ensure scalable, production‑ready solutions.

Skills

Python

SQL

Agile development

Communication

Collaboration

Data analysis

Education

Master's or PhD in CS/Math/Engineering

10+ years in ML/AI

Tools

Databricks

SAP Datasphere

SAP HANA Cloud

SAP Graph API

SPARQL

Job description

SAP is building an enterprise AI context engine within the Data and Applied Science team. You will translate business challenges into concrete AI designs, develop end‑to‑end ML solutions, and collaborate with product, engineering, and customer teams to deliver scalable, production‑ready outcomes.

The role emphasizes deep SAP data knowledge, semantic modeling, and cutting‑edge AI capabilities across ERP‑related domains, shaping SAP's AI future.