Senior Data Scientist - Procurement Analytics

Role Overview: As a Senior Data Scientist - Procurement Analytics at AB InBev GCC, you will be an integral part of the procurement technology project team. Your role will involve applying Generative Artificial Intelligence to develop and implement innovative solutions using generative AI technologies, contributing to optimizing business operations and enhancing customer experience through advanced technological solutions.

Key Responsibilities: - Design, develop, and maintain end-to-end software solutions using generative AI technologies and machine learning within the logistics technology department. - Utilize low/no-code tools as accelerators for development and solution implementation. - Integrate and work with SAP systems to ensure seamless data flow between procurement and logistics operations. - Familiarity with Model Context Protocol (MCP) to structure, manage, and optimize data exchange between applications and ML models. - Develop and deploy applications using Python and Machine Learning (ML) stack to automate invoice validation, anomaly detection, and data analysis. - Collaborate with cross-functional teams to gather requirements, propose technical solutions, and align deliverables with business needs. - Implement and maintain deployment pipelines, leveraging Azure DevOps for CI/CD automation. - Ensure solutions meet compliance, security, and performance standards. - Conduct code reviews and enforce best practices in software engineering. - Maximize scalability, performance, usability, and reliability of developed applications. - Document technical designs, workflows, and processes for both technical and non-technical stakeholders. - Support and troubleshoot production issues, ensuring minimal downtime and quick resolution. - Systematically analyze continuous improvement opportunities in already developed systems. - Demonstrate initiative for autonomous learning and constant updates on emerging technologies. - Actively participate in Scrum events and ensure commitment to agreed schedules and deliveries.

Qualifications Required: - Education: Bachelors degree in Computer Science, Software Engineering, Information Systems, or related field. - Experience: Minimum of 5 years of hands-on experience as a Software Engineer, with a proven track record of delivering high-quality, scalable, and maintainable solutions in a collaborative team environment. - Mandatory Skills: Strong proficiency in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), familiarity with Model Context Protocol (MCP), containerization (Docker, Kubernetes), experience in application development and deployment in production environments, experience with cloud platforms (preferably Azure), strong problem-solving skills, excellent communication skills, ability to work collaboratively in a fast-paced, agile environment. - Preferred Skills: Professional experience in the Consumer-Packaged Goods (CPG) sector, previous work under Agile methodology and Scrum framework, familiarity with Azure DevOps and CI/CD pipelines, knowledge of procurement systems and processes.

Join AB InBev GCC and be part of a team that dreams big, just like you do! Role Overview: As a Senior Data Scientist - Procurement Analytics at AB InBev GCC, you will be an integral part of the procurement technology project team. Your role will involve applying Generative Artificial Intelligence to develop and implement innovative solutions using generative AI technologies, contributing to optimizing business operations and enhancing customer experience through advanced technological solutions.

Key Responsibilities: - Design, develop, and maintain end-to-end software solutions using generative AI technologies and machine learning within the logistics technology department. - Utilize low/no-code tools as accelerators for development and solution implementation. - Integrate and work with SAP systems to ensure seamless data flow between procurement and logistics operations. - Familiarity with Model Context Protocol (MCP) to structure, manage, and optimize data exchange between applications and ML models. - Develop and deploy applications using Python and Machine Learning (ML) stack to automate invoice validation, anomaly detection, and data analysis. - Collaborate with cross-functional teams to gather requirements, propose technical solutions, and align deliverables with business needs. - Implement and maintain deployment pipelines, leveraging Azure DevOps for CI/CD automation. - Ensure solutions meet compliance, security, and performance standards. - Conduct code reviews and enforce best practices in software engineering. - Maximize scalability, performance, usability, and reliability of developed applications. - Document technical designs, workflows, and processes for both technical and non-technical stakeholders. - Support and troubleshoot production issues, ensuring minimal downtime and quick resolution. - Systematically analyze continuous impr