Job Description The Data Scientist develops advanced analytics, machine learning models, and AI-driven solutions that enable predictive insights and intelligent decision-making across procurement. The role transforms procurement data into analytical capabilities that support sourcing strategies, supplier risk monitoring, spend optimization, and procurement performance management. Working closely with data engineering and analytics product teams, this position designs and deploys analytical models and AI-enabled solutions that leverage procurement data to generate scalable insights. The role also contributes to the development of agent-based AI solutions that automate analytical workflows and enhance procurement intelligence. Main Responsibilities • Develop predictive models, simulations, and advanced analytics supporting procurement decision-making, supplier risk monitoring, and sourcing strategies • Apply statistical analysis and machine learning techniques to identify patterns, risks, and opportunities within procurement datasets such as spend, supplier performance, and inventory information. • Design and develop AI-driven analytical solutions, including intelligent agents and multi-agent workflows that automate procurement intelligence activities such as supplier analysis, risk detection, and decision support. • Prototype and deploy advanced analytics and AI use cases that enhance procurement insights and strategic decision-making. • Collaborate with data engineers to access, structure, and prepare procurement datasets required for analytical modeling and AI applications. • Partner with procurement analytics product teams to operationalize models and AI capabilities into dashboards, decision-support tools, and analytical applications. • Monitor and continuously improve analytical models and AI solutions to ensure accuracy, reliability, and business relevance. Position Challenges • Translating complex procurement data into analytical models that generate actionable business insights. • Developing predictive and AI-driven solutions that remain interpretable and useful for procurement stakeholders. • Collaborating effectively across technical teams (data engineering, analytics) and procurement business teams. • Identifying high-value opportunities where advanced analytics and AI can improve procurement decision-making. • Managing evolving analytical requirements in a rapidly changing digital and AI landscape. Qualifications Languages • English: Advanced. Academic Background • Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Artificial Intelligence, or related analytical fields. Areas of Expertise • Experience in data science, full-stack development, machine learning, or advanced analytics roles supporting business decision-making (3-6 y) • Experience developing predictive models, statistical analysis, and machine learning applications using large and complex datasets. • Experience applying analytics or AI solutions to operational or business decision processes. Technical Skills • Strong programming skills in Python and experience working with analytical libraries for data science and machine learning. • Experience applying machine learning, statistical modeling, and predictive analytics techniques to real-world business problems. • Advanced SQL skills for data manipulation and analysis of large transactional datasets. • Experience developing AI-enabled analytical solutions, including the use of large language models (LLMs), retrieval-augmented generation (RAG), and AI agents or multi-agent workflows to automate analytical tasks or decision-support processes. • Familiarity with modern data platforms and analytics environments (e.g., cloud data warehouses, data lakes, or similar analytical infrastructures). Soft Skills • Strong analytical thinking and structured problem-solving capabilities. • Ability to translate complex analytical outputs into clear insights for business stakeholders. • Effective collaboration with both technical teams (data engineering, analytics) and procurement stakeholders • Curiosity and experimentation mindset with interest in emerging analytics and AI technologies. Internal/External Relations Internal • Global Procurement Leadership • Regional Procurement Organizations • Procurement Analytics & Product Teams • Enterprise Data Engineering and Data Architecture teams • IT / P&IT Data Platform teams External • Data platform vendors and technology partners • Data and analytics consultants supporting enterprise initiatives • Mckinsey CEMEX Diversity and Inclusion Statement At CEMEX, we recognize the diversity of the world in which we live and in which we do business. We respect diversity, we address the inclusion and non-discrimination of any talented person, regardless of gender, physical ability, age, sexual orientation, culture, ethnicity, religion, political affiliation, marital status, pregnancy / maternity / paternity and nationality. We promote a culture of equity for the construction of a sustainable business and the well-being and development of CEMEX employees.