Forward Deployed Senior Data Scientist

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 In this role, you will design, develop, and apply advanced data science, statistical, and machine learning methods to solve complex business problems. Embedded within customer engagements and fast-paced delivery teams, you will translate business challenges into scalable analytical and AI solutions that deliver measurable outcomes. Working closely with customers, engineers, and product teams, you will build production-ready machine learning and Generative AI solutions while continuously improving model quality, performance, and business impact. In this role, you will: • Transform business challenges into data-driven solutions by identifying analytical opportunities, exploring data, engineering features, and developing predictive models. • Design, develop, train, evaluate, and optimize machine learning models and statistical solutions for enterprise business scenarios. • Apply techniques across exploratory data analysis, forecasting, classification, clustering, recommendation systems, anomaly detection, experimentation, causal analysis, and predictive analytics. • Develop Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and Agentic AI frameworks. • Integrate analytical and AI solutions into enterprise applications and business processes, ensuring scalability, robustness, and production readiness. • Define evaluation metrics, validate model performance, monitor deployed models, and continuously improve solution accuracy and reliability. • Work closely with customer teams to understand business processes, data landscapes, and operational challenges to co-create impactful AI solutions. • Collaborate with AI Engineers, Data Engineers, Product Managers, and UX teams to deliver end-to-end AI products. • Communicate analytical findings, technical trade-offs, and solution recommendations clearly to engineering teams and customer stakeholders. • Stay current with the latest advancements in Data Science, Machine Learning, Generative AI, and Agentic AI, applying emerging techniques where appropriate. What you bring • Strong hands-on expertise in Data Science, Machine Learning, and Applied AI with excellent proficiency in Python and SQL. • Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar technologies. • Strong understanding of statistics, probability, hypothesis testing, experimental design, model evaluation, and feature engineering. • Experience developing predictive models, recommendation systems, forecasting models, anomaly detection, and classification algorithms. • Hands-on experience with Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen. • Experience deploying machine learning and AI solutions using cloud-native platforms and modern MLOps practices. • Familiarity with SAP data landscapes including SAP S/4HANA, SAP HANA Cloud, SAP BW/4HANA, SAP Business Technology Platform (BTP), AI Core, AI Launchpad, and SAP AI services is an advantage. • Ability to translate ambiguous business requirements into practical analytical solutions while balancing model accuracy, interpretability, scalability, and business value. • Strong communication, collaboration, and problem-solving skills with the ability to work effectively in customer-facing environments. • You proactively leverage AI in your everyday workflows, ensuring high-quality outcomes through thoughtful context design, experimentation, and system integration. Where you belong You will be part of a growing AI and industry expert team dedicated to serving customers across the Americas, Europe, and Asia. We bring together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate and lead in their markets. You’ll collaborate with cross-functional teams to solve challenging business problems, build enterprise-grade AI solutions, and deliver measurable customer value. This is a place for curious builders who enjoy learning, experimenting, and applying AI to real-world business challenges. #SAPIndustryAICareers #SAPAICareers Bring out your best SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Origi

Strong hands-on expertise in Data Science, Machine Learning, and Applied AI with excellent proficiency in Python and SQL. Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar. Strong understanding of statistics, probability, hypothesis testing, experimental design, model evaluation, and feature engineering. Experience developing predictive models, recommendation systems, forecasting models, anomaly detection, and classification algorithms. Hands-on experience with Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and AI orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen. Experience deploying machine learning and AI solutions using cloud-native platforms and modern MLOps practices. Familiarity with SAP data landscapes including SAP S/4HANA, SAP HANA Cloud, SAP BW/4HANA, SAP Business Technology Platform (BTP), AI Core, AI Launchpad, and SAP AI services is an advantage. Ability to translate ambiguous business requirements into practical analytical solutions while balancing model accuracy, interpretability, scalability, and business value. Strong communication, collaboration, and problem-solving skills with the ability to work effectively in customer-facing environments. Proactive use of AI in everyday workflows to ensure high-quality outcomes through thoughtful context design and system integration.

Transform business challenges into data-driven solutions by identifying analytical opportunities, exploring data, engineering features, and developing predictive models. Design, develop, train, evaluate, and optimize machine learning models and statistical solutions for enterprise business scenarios. Apply techniques across exploratory data analysis, forecasting, classification, clustering, recommendation systems, anomaly detection, experimentation, causal analysis, and predictive analytics. Develop Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector databases, and Agentic AI frameworks. Integrate analytical and AI solutions into enterprise applications and business processes, ensuring scalability, robustness, and production readiness. Define evaluation metrics, validate model performance, monitor deployed models, and continuously improve solution accuracy and reliability. Work closely with customer teams to understand business processes, data landscapes, and operational challenges to co-create impactful AI solutions. Collaborate with AI Engineers, Data Engineers, Product Managers, and UX teams to deliver end-to-end AI products. Communicate analytical findings, technical trade-offs, and solution recommendations clearly to engineering teams and customer stakeholders. Stay current with the latest advancements in Data Science, Machine Learning, Generative AI, and Agentic AI, applying emerging techniques where appropriate.