AI Data Lead - SAP-RPT Model Family (f/m/d)

Responsibilities

• Ownership of Data Assets & strategy: Own pre‑training, evaluation, and meta‑data including proprietary, open‑source, and synthetic datasets. Develop and execute vision.
• End‑to‑End Execution: Lead data extraction, curation, and quality analysis to produce high‑impact training signals. Set technical priorities and define work packages across teams to ensure high‑quality outcomes.
• Drive Partnership: Work closely with science leads to define data requirements and co‑design the datasets necessary to push model capabilities. Build strong alliances with internal data and technology providers.
• Deep‑Dive Data Exploration: Explore and analyse datasets to identify patterns, edge cases, and quality issues that inform model development.
• Data Architecture: Influence data architecture decisions to ensure seamless data access for both model training and production environments.

Qualifications

• Education & Experience: PhD or Master’s degree in Computer Science, AI, or a relevant field, followed by 7+ years of professional experience in high‑scale data environments.
• Functional Leadership: Proven track record of leading large‑scale, end‑to‑end technical projects, ideally with data and machine‑learning deliverables.
• SAP Data Expertise: Profound understanding of SAP’s relational business data, including key business objects and underlying table structures. Ability to navigate semantic models (e.g., VDM, CDS, OData) and possess sophisticated knowledge of the complex business logic and relational schemas inherent in the enterprise landscape.
• Data Engineering & SAP Ecosystem: Extensive experience with high‑performance databases (SQL) and SAP’s data stack (e.g., BDC, HANA & BTP) as well as with the development of cloud‑native pipelines. Strong Python skills and ideally exposure to Knowledge Graphs (including technologies like RDL).
• Machine Learning Skills: Solid ML knowledge with practical experience in solving real‑world problems with AI – ideally in the tabular domain.
• Organizational Influence: Ability to build partnerships with internal technology providers and lead cross‑team technical initiatives and task prioritization.

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