Lead Data Scientist – Sustainability Focus

• Provide technical leadership for the support, evolution, and reliability of Nestlé Brazil’s Data Science, Machine Learning, and Artificial Intelligence products.
• Ensure the availability, performance, scalability, security, and operational continuity of models, Machine Learning pipelines, and analytical applications in production.
• Take ownership of the operation and support of the analytical and AI model portfolio, ensuring SLAs, incident resolution, and continuous improvement.
• Provide technical leadership to teams responsible for supporting and evolving data and AI products, defining priorities, technical direction, and quality standards.
• Serve as a technical reference for Data Science, Machine Learning Engineering, and MLOps teams.
• Establish and enhance monitoring and observability for data, models, pipelines, and inference services.
• Ensure model quality, relevance, and performance through monitoring, validation, retraining, and lifecycle governance.
• Lead demand prioritization and negotiation, aligning expectations, risks, timelines, and solution value.
• Connect business areas, suppliers, and technical teams, promoting alignment and data-driven decision-making.
• Contribute to technological advancement, optimization, operational efficiency, scalability, and cost rationalization across AI environments.
• Promote technical development, collaboration, knowledge sharing, and operational excellence among internal teams and partners.

• Bachelor’s degree in Technology, Engineering, Mathematics, Statistics, or a related field.
• Experience providing technical leadership or managing teams in Data Science, Machine Learning Engineering, Artificial Intelligence, or related areas, ensuring technical quality, SLA compliance, and results delivery.
• Experience supporting, operating, and evolving Machine Learning models, AI products, and analytical applications in corporate environments.
• Experience in Machine Learning Engineering, MLOps, and production model lifecycle governance, including version control, CI/CD, model monitoring, and retraining.
• Experience with monitoring, observability, operational reliability, and incident management for AI and Machine Learning solutions.
• Experience with Python, SQL, and modern Data Science and Machine Learning ecosystems.
• Experience with Analytics and AI platforms such as Databricks, Snowflake, or equivalent technologies.
• Ability to translate business needs into technical direction and lead discussions with stakeholders at different levels.
• Strong communication, influencing, and negotiation skills with technical audiences, business areas, external partners, and executives.
• Experience managing competing priorities and coordinating initiatives across multiple teams and suppliers.
• Experience collaborating with Data Engineering, Architecture, Governance, Security, and Data Product teams.
• Advanced or fluent English.