Senior Researcher in Embedded Research for AI in Finance (f/m/d)

In this role you will help bridge academia and SAP to advance AI in Finance. You’ll contribute to AI use case ideation, development, and adoption across SAP Finance, translating research insights into scalable product concepts. You will work with cross-functional teams to validate capabilities and support go-live readiness, while mentoring researchers and shaping SAP’s research strategy in quantitative finance. This is a collaborative, innovation-driven opportunity at scale with meaningful impact on enterprise finance.

• great benefits
• team growth and success
• focus on wellbeing
• flexible working models
• opportunity to grow and succeed
• inclusion and health initiatives

• Ideate, develop, and adopt AI use cases for Finance transformation challenges
• Prototype AI models and agents for Finance processes and risk quantification
• Translate empirical research into scalable finance innovation strategies
• Collaborate with GFA Operations, business and technology teams to define requirements and validate AI outputs
• Support knowledge transfer and capability building within Finance teams
• Drive cross-functional alignment of AI initiatives with business priorities
• Shape strategic AI roadmap for Finance adoption across the enterprise
• Mentor and participate in interdisciplinary research activities within SAP PhD programs
• Facilitate stakeholder workshops to collect requirements and build implementation roadmaps
• Bridge academic findings with industry needs to influence product directions

• Advanced university degree (PhD) in finance, management, information systems, technology management, quantitative economics, or similar
• 2+ years of industry-relevant research experience; consulting at the intersection of Finance and ML is a plus
• Track record of applied Finance research with industry exposure; publications preferred
• Proven experience building and deploying ML models in Finance (risk monitoring tools)
• Strong Python skills for financial data analysis; experience with large datasets, web scraping, and libraries like PyTorch, sklearn, numpy, pandas
• Hands-on experience prototyping agentic AI solutions and familiarity with prompt engineering, RAG, tool-augmented AI
• Ability to work on challenging research topics with a scientific approach
• Strong collaboration and communication skills in English
• Sound understanding of SAP’s strategy
• Willingness to translate research directions into product functionality

• Collaborative mindset
• Structured, scientific thinking
• Strong written and verbal communication
• Python for financial data analysis (PyTorch, scikit-learn, NumPy, pandas)
• Docker, Linux, VS Code
• Agentic AI concepts, LLMs, prompt engineering, RAG