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

About the job

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.

What you`ll build:
The Academic Partnerships organization at SAP partners with other SAP teams to provide the best services to foster strategic research collaborations between SAP and academia. The PhD Graduate Team is responsible for building the bridge between cutting-edge research and SAP functional teams. Our mission is to facilitate the application of research across SAP and contribute to SAP research strategy with interdisciplinary research activities.

Working together with the Strategy & Operations Team for SAP Finance, focusing on AI adoption and transformation in SAP’s finance processes and corporate decision-making, you will bring the research perspectives and insights from finance, machine learning, and AI adoption research to our product innovation strategy, validating the impact of AI technologies, and bridging the gap between industry and academia.

The Role:

In your daily work you will work on AI use case ideation, development, and adoption for Finance transformation challenges, collaborating with industry experts, researchers, and business stakeholders. You will combine hands-on data science work with close collaboration with GFA business teams to translate innovation and research findings into actionable AI use cases. Drawing on your background in Finance research (incl. asset pricing, shareholder behavior, AI adoption, or similar), you will help validate and scale AI capabilities across Finance workstreams, bridge academic insights and enterprise requirements, and contribute to SAP's research strategy in quantitative Finance:

The position involves working within a highly motivated team of experts, driving innovation in a collaborative research environment, with close collaboration across lines of business and strong potential to influence future product directions and innovation at scale.

• Apply machine learning and quantitative research methods to Finance AI use cases within SAP's AI innovation programs in GFA
• Prototype AI models and agents for Finance processes, drawing on experience with risk quantification, and shareholder behavior analysis
• Translate empirical research findings into concrete, scalable Finance innovation strategies
• Collaborate with GFA Operations, business stakeholders, and technology teams to define requirements, validate AI capabilities, and support go-live readiness
• Support knowledge transfer and capability building within Finance teams, leveraging experience teaching and supervising researchers in quantitative methods
• Drive cross-functional collaboration across Product, IT, Finance, and leadership teams to align AI initiatives with business priorities and ensure end-to-end delivery from research insight to production
• Shape a strategic vision for AI in Finance by identifying high-impact application areas and building a roadmap for their adoption across the enterprise
• Facilitate structured stakeholder workshops and review sessions to gather Finance requirements, validate AI outputs, and build consensus on implementation roadmaps
• Bridge the gap between academic findings and industry
• Participate in interdisciplinary research activities with the PhD graduate team, supporting SAP’s research strategy
• Be an active part of research mentoring programs and the research community at SAP
• Collaborate with various internal and external stakeholders

What you bring:

• Advanced university degree (PhD relevant to industrial context preferred, dissertation focused on AI applications preferred) in finance, management, information systems, technology management, quantitative economics, or similar
• 2+ years of work experience in industry-relevant research, additional experiences in consulting at the intersection of Finance and ML, budget responsibility preferred
• Track record of applied Finance research (publications preferred) at the intersection of industry and academia, with conference presentations and industry exposure in investment management and M&A, as well as in LLM and ML applications across Finance areas
• Academic track record in related fields of research
• Proven experience building and deploying ML models in a Finance context — including risk monitoring tools, and solid understanding of AI adoption concepts
• Strong programming skills in Python for financial data analysis, including experience with large datasets, web scraping, model training. Packages incl. pytorch, sklearn, numpy, pandas; tools like Docker, Github, Linux, VSCode
• Hands-on experience prototyping agentic AI solutions and leveraging LLMs in research or applied projects is a plus; familiarity with prompt engineering, RAG, or tool-augmented AI workflows
• Ability to work on challenging research topics with a structured, scientific approach
• Academic track record in related fields of research
• Sound understanding of SAP’s strategy
• Strong hands-on mindset and willingness to translate promising research direction into product functionality
• Strong collaboration skills and a team-oriented mindset
• Experience working in enterprise-relevant research projects in Finance
• Good written and verbal communication skills in English

Where you belong:

The Academic Partnership organization at SAP is the bridge connecting SAP and academia. We build collaborative, structured partnerships with academic institutions and encompass a wide range of activities and programs in regards of academic teaching, academic community management, and PhD talent management.

The PhD Graduate Team stands for embedding cutting-edge research into functional teams across SAP, bringing together interdisciplinary PhD talent in a research-like environment.

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