Data Science Expert

Job description

**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** We are seeking a highly accomplished AI / Data Science Expert to lead the design, strategy, and deployment of advanced AI and machine learning solutions at scale. This role requires deep technical mastery, thought leadership, and the ability to shape enterprise-wide data and AI initiatives. The ideal candidate will combine cutting-edge expertise with strong business acumen—including hands-on experience with agentic AI systems and enterprise AI governance—to drive transformational outcomes and innovation across the orgaization. - Define and drive the enterprise AI/ML strategy, aligning advanced analytics initiatives with business objectives and long-term vision. - Architect and oversee the development of complex, large-scale machine learning and deep learning systems for high-impact use cases. - Act as a technical authority and thought leader, guiding best practices, frameworks, and standards for AI and data science across teams. - Translate ambiguous, high-level business challenges into innovative, scalable, and production-ready data science solutions. - Lead the design of robust, end-to-end data ecosystems, including data pipelines, feature stores, and model lifecycle management. - Drive innovation through exploration of emerging AI techniques, including generative AI, large language models, and advanced deep learning architectures. - Design and build scalable multi-agent frameworks, leveraging industry-standard agentic protocols such as Agent-to-Agent (A2A) and Model Context Protocol (MCP) to enable robust, interoperable orchestration across distributed agent networks. - Ensure model reliability, explainability, fairness, and governance aligned with enterprise and regulatory standards. - Champion AI security best practices, including the design and enforcement of guardrails, prompt safety mechanisms, and trust boundaries for agentic and LLM-based systems operating in production environments. - Mentor and guide senior data scientists and engineers, fostering technical excellence and continuous learning. - Influence executive stakeholders and decision-making by clearly communicating complex findings, trade-offs, and strategic recommendations. - Champion MLOps best practices, ensuring scalable deployment, monitoring, and lifecycle management of models in production environments. **What You Bring** - Deep, expert-level expertise in AI and data science with specialization in areas such as NLP, computer vision, or generative AI. - Extensive experience designing and deploying large-scale machine learning systems in production environments. - Mastery of modern AI/ML frameworks and platforms, with strong hands-on proficiency in Python, SQL, and distributed data processing technologies (e.g., Databricks, Spark). - Strong foundation in advanced statistical modeling, optimization techniques, and algorithm design. - Demonstrated experience architecting and deploying scalable multi-agent AI systems, with working knowledge of industry-standard agent interoperability protocols including A2A (Agent-to-Agent) and MCP (Model Context Protocol). - Familiarity with AI security principles and guardrail frameworks for agentic and generative AI systems, including prompt injection defense, output validation, and policy-based access controls for autonomous agents is highly desirable. - Proven experience architecting data platforms, including data lakes, pipelines, and real-time processing systems. - Expertise in enterprise-grade databases such as SAP HANA, SQL Server, or Oracle. - Experience with SAP Business Technology Platform (BTP) and enterprise AI integration is highly desirable. - Demonstrated ability to lead complex, cross-functional initiatives and influence senior leadership. - Strong track record of innovation, including introduction of new methodologies, tools, or AI capabilities. - Exceptional communication and storytelling skills, with the ability to translate complex technical concepts into strategic insights. **Where you belong** Within the Cloud Lifecycle Engineering and AIOps (CLEO) organization of Global Cloud Operations (GCO), the Core AI Team—at the heart of the AI Foundation Team—drives the vision of an AI-powered autonomous enterprise, redefining how operations are designed, executed, and continuously optimized at scale. As a strategic cornerstone, the team embeds intelligent, self-learning capabilities into core processes, enabling adaptive, self-healing, and increasingly autonomous operations. With a bold mandate to transform GCO through advanced artificial intelligence and data management, the AI Foundation Team builds resilient, enterprise-grade AI foundations powered by best-in-class machine learning. By working across all GCO organizations, we accelerate the evolution from reactive to predictive and ultimately autonomous operations—delivering real-time intelligence, seamless automation, and sustained operational excellence. **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 empl