Description: * Bachelor's degree in Statistics, Engineering, Economics, Mathematics, Computer Science, Actuarial Science, or related fields. * Experience in AI and Data. * Extensive experience building, developing, and monitoring real-world AI models (personalization, optimization, or forecasting). * In-depth knowledge of ML techniques, probability and statistics, experimental design, optimization, and causal inference for A/B testing. * Solid understanding of machine learning concepts: regression, classification, clustering, neural networks, feature selection, cross-validation, model evaluation, etc. * Knowledge of software development best practices and data engineering, including awareness of challenges involved in operationalizing ML models (MLOps). * [Desirable] Leadership experience with data professionals (analysts, scientists, or engineers). * Experience in cloud-based development (GCP and AWS preferred). * Excellent communication skills to discuss complex technical topics with both technical and non-technical audiences. * Ability to organize and plan, with skill in managing multiple priorities and delivering results in dynamic environments. Differentiators: * Experience with models applied to sales (recommendation, segmentation, churn, etc.); * Experience with Computer Vision models; * Experience with Machine Learning Engineering. * People management: develop, mentor, and retain high-performing data science teams; * Promote excellence in work execution and maintain well-being and collaboration within a multidisciplinary and decentralized (on-site/remote) team. * Strategic leadership: define and lead short- and medium-term data science team strategy, ensuring alignment with company objectives and stakeholders’ interests; * Participate in structuring business problems with Operations, Projects, and IT teams to prioritize and deliver data products with business impact; * Serve as a technical reference for the team and the company—someone capable of driving innovation through data, technology, and AI. * Assist business teams in interpreting results and provide recommendations to improve processes, ensuring proper measurement of outcomes. 2512170202551922268