Junior Data Scientist (Domain Models) - Data Labs (m/f/d)

SAP SE; Garching bei München; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

SAP SE is seeking an early‑career Data and Applied Scientist to help build a semantic foundation for enterprise AI. You'll work with senior scientists to ground AI solutions in SAP's business data and ontology, shaping AI across Order-to-Cash, Procure-to-Pay, and other processes.

Join a team focused on context engineering, RAG pipelines, embeddings, and scalable AI workflows using Databricks, SAP Datasphere, and cloud platforms. Grow from day one in a globally impactful role.

Qualifikationen

• Bachelor's or Master's in Computer Science, Applied Mathematics, Statistics, Engineering, or related field.
• Foundational understanding of knowledge representation, semantic data systems, or graph databases.
• Familiarity with SPARQL, Cypher, or GQL; RDF vs property graphs familiarity is a plus.
• Exposure to GenAI concepts: RAG, embeddings, vector databases, semantic retrieval.
• Proficiency in Python and SQL; experience with PyTorch, TensorFlow, or scikit-learn.
• Willingness to learn production-grade development practices and end-to-end AI solutions.
• Strong written and verbal communication and teamwork.

Aufgaben

• Collaborate with product, engineering and business teams to translate complex challenges into AI solutions.
• Apply ML and semantic techniques to build AI solutions using enterprise data and knowledge graphs.
• Learn SAP data models, metadata structures, and business process semantics to ground AI in real enterprise context.

Kenntnisse

Quantitative background

Knowledge graphs

Graph databases

GenAI concepts

Python

SQL

Production-grade development

Communication

Ausbildung

Bachelor's or Master's in CS/Math/Engineering

Tools

SPARQL

Cypher

GQL

OWL

RDF/RDFS

Jobbeschreibung

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

The context engine that makes AI enterprise ready.

Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest enterprise data and process context in the world. As a Data and Applied Scientist at SAP, you'll help build the context engine grounded in SAP's Business Ontology: the semantic infrastructure that transforms raw business data into the knowledge layer powering SAP's AI agents and assistants.

This is an early-career role for engineers and scientists who are sharp, curious, and ready to do real work on hard problems from day one.

You'llcontribute to the semantic and contextual foundation of SAP's AI. While generic AI agentsoperateon surface-level patterns, SAP agents areaccuratebecause they understand the real semantics of enterprise business master data, process flows, and domain relationships.You'llwork alongside senior scientists and engineers to build and scale the layer that makes that possible.

Support the design and maintenance of enterprise ontologies and semantic models that give AI agents accurate, grounded understanding of SAP and connected business landscapes — learning how data from SAP, Salesforce, Workday, ServiceNow, MES/IoT systems, and external providers gets harmonized into unified semantic layers.

Contribute to AI capabilities including RAG pipelines, embeddings, vector databases, and enterprise knowledge grounding that make SAP's agentsaccurateand reliable in production.

Develop and iterate on AI solutions — including generative AI and LLM-based approaches — using enterprise business data, knowledge graphs, business process intelligence, and structured and unstructured data assets.

Learn SAP's deep data and process context — data models, metadata structures, and business process semantics across Order-to-Cash, Procure-to-Pay, Record-to-Report, and Plan-to-Produce — and apply that context to ground AI solutions in real enterprise reality.

Work with modern cloud and data platforms including Databricks, SAP Datasphere, SAP HANA Cloud, AWS, Azure, and GCP, gaining hands‑on experience with scalable AI workflows.

Collaborate across product, engineering, and business teams to understand how ambiguous business challenges get translated into concrete AIsolutions, andcontribute meaningfully to that process from early stages through deployment.

Apply machine learning, deep learning, and statistical modeling to build and evaluate AI solutions using real-world enterprise datasets.

Required Qualifications

Bachelor's or Master's in Computer Science, Applied Mathematics, Statistics, Engineering, or a related quantitative field — recent graduates welcome.

Foundational understanding of knowledge representation, semantic data systems, or graph databases (through coursework, research, or personal projects).

Familiarity with at least one graph query language (SPARQL, Cypher, or GQL) or a willingness to learn quickly; some exposure to the trade-offs between RDF triple stores and property graph databases is a plus.

Exposure to modern GenAI concepts — RAG, embeddings, vector databases, semantic retrieval — through coursework, research, or hands‑on experimentation.

Solid Python and SQL skills; some experience with ML libraries such as PyTorch, TensorFlow, or scikit-learn (academic projects, research work, and personal projects all count).

Eagerness to learn production‑grade development practices and grow into operating AI/ML solutions end‑to‑end.

Clear, collaborative communication style — you ask good questions, explain your thinking, and work well with others.

Preferred Qualifications

Hands‑on experience — through internships, research, or projects — with ontology design, semantic modeling, or knowledge graphs.

Any exposure to enterprise software ecosystems (SAP, Salesforce, Workday, ServiceNow, or similar) is a real accelerator here.

Familiarity with the W3C stack (OWL, RDF/RDFS, SKOS, SHACL) or property graph query languages (Cypher, GQL).

Academic or project experience in machine learning and deep learning, including training, evaluating, and improving models on real datasets.

Curiosity about agentic AI, reasoning frameworks, multi‑agent architectures, or planning and orchestration.

Experience contributing to shared or reusable codebases — open‑source projects, research codebases, or team projects.

Where you belong

The Application AI team sits at the foundation layer - We build the LLM systems and intelligent infrastructure that run across SAP's global platforms, which means the work you do here doesn't just influence one product, it sets the direction for how AI operates at enterprise scale. A core part of that challenge is making AI genuinely understand the business not just process text, but reason over richly structured enterprise data through robust data ontologies and semantic knowledge frameworks that give models real context about how SAP's world is organized. This is a team that values engineers who think like owners: people who want to define the architecture, not just implement a spec.You'llwork in an environment designed around trust and autonomy, where the expectation is that you move fast, make calls, and drive outcomes without layers of approval slowing you down.

AI skills used in this role

Agentic AI Day‑to‑Day Practice, AI Adoption Capability, AI Output Quality Assurance, Context Engineering, AI‑Assisted Automation and Prototyping, Learning Agility, Creative Thinking, Complex Problem Solving, Effective Communication, Collaboration, Agentic Orchestration, Data Engineering, Deep Learning, Model Training, Semantic Retrieval

Bring out your best

SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end‑to‑end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose‑driven and future‑focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.

We win with inclusion

SAP’s culture of inclusion, focus on health and well‑being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate your website or to complete your application, please send an e‑mail with your request to Recruiting Operations Team: [e-mail].

For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program , according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

Work Area: Software‑Design and Development

Expected Travel: 0 - 10%

Career Status: Graduate

Employment Type: Regular Full Time

Location: Garching bei München (Munich), DE, 85748

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