Data Scientist - Focus on SAP MM Procurement

Accountabilities: Design, develop, and implement artificial intelligence and machine learning capabilities for global procurement solutions. Integrate AI functionality into existing SAP Materials Management (SAP MM) applications and contribute to the development of new AI-powered user experiences. Leverage data, APIs, enterprise systems, and cloud technologies to translate business challenges into scalable technical solutions. Explore, develop, and implement generative AI, Large Language Model (LLM), and Retrieval-Augmented Generation (RAG) solutions tailored to procurement use cases. Contribute to application architecture, software evolution, and the adoption of modern AI-first engineering approaches. Collaborate with software engineers, product teams, and business stakeholders to understand user needs and deliver effective technology solutions. Support the implementation of best practices in software engineering, AI development, MLOps, data quality, and data governance. Experiment with emerging technologies, challenge conventional approaches, and identify opportunities to improve procurement processes through intelligent automation. Help ensure AI-powered enterprise solutions are scalable, reliable, maintainable, and aligned with responsible AI principles. Requirements: Bachelor's degree or equivalent higher education qualification in Computer Science, Software Engineering, Data Science, Information Systems, or a related discipline. Advanced English proficiency, with the ability to communicate effectively and collaborate in an international working environment. Availability to work in a hybrid model, with on-site presence in Indaiatuba, São Paulo, three days per week. Practical experience with Python, SQL, statistics, probability, and machine learning concepts. Knowledge of data engineering fundamentals, including experience or familiarity with Databricks, Apache Spark, and cloud platforms such as Microsoft Azure or AWS. Experience with generative AI, LLMs, RAG architectures, and API integrations. Familiarity with MLOps practices, data visualization tools such as Power BI or Tableau, data governance, data quality, Git, and GitHub. Strong analytical and problem-solving skills, with the ability to translate business requirements into practical technical solutions. Collaborative communication skills and the ability to work effectively with multidisciplinary teams in a global environment. Adaptability, curiosity, and a willingness to experiment with emerging technologies and continuously improve engineering practices. Preferred qualifications: Experience with multi-agent systems, AI solution architecture, or Natural Language Processing (NLP). Knowledge of vector databases and search technologies such as OpenSearch, Pinecone, or Azure AI Search. Experience with deep learning, containerization, and software architecture principles or design patterns. Understanding of responsible AI, AI governance, and the development of scalable AI-powered enterprise applications. Benefits: Variable compensation: Additional compensation opportunities based on the company's applicable compensation program. Health insurance: Medical coverage. Dental plan: Dental care coverage. Life insurance: Financial protection through life insurance coverage. Private pension plan: Support for long-term financial planning. Vision care benefit: Support for vision-related needs. Vaccination reimbursement: Reimbursement for eligible vaccination expenses. Professional development: Access to a corporate university for continued learning and skills development. Well-being and fitness: Access to TotalPass. Food benefits: Depending on the location, access to an on-site cafeteria, meal vouchers, or a food allowance. Pharmacy assistance: Support for eligible pharmacy-related expenses. Hybrid flexibility: A hybrid work arrangement combining remote work with three days per week on-site in Indaiatuba, São Paulo. Additional benefits: Other benefits may be available under the company's applicable policies.