Job Description: * Bachelor's degree in Statistics, Engineering, Economics, Mathematics, Computer Science, Actuarial Science, or related fields; * Preferred: Master's or Ph.D. in Statistics, Economics, Operations Research, or related fields; * Experience building classification models in business environments (e.g., fraud detection, churn prediction, purchase propensity, risk assessment, etc.); * Experience with unsupervised models for segmentation/clustering; * Ability to structure problems: translate business problems into well-defined machine learning problems; * Preferred: Experience in retail or financial sectors; * Preferred: Proficiency in validating model performance using business metrics—not only technical metrics; * Predictive models: Logistic regression, Random Forest, XGBoost, CatBoost, LightGBM, etc.; * Python: Proficiency in data manipulation and transformation using Pandas and NumPy; strong experience building and evaluating models using libraries such as Scikit-learn, XGBoost, and/or TensorFlow/PyTorch; ability to write clean, modular, and version-controlled code (Git); * Preferred: Cloud experience (AWS, GCP, or Azure): Must be able to provision resources and work with key services such as BigQuery (advanced queries, performance tuning), Cloud Storage (data management), and ideally Vertex AI (model training and deployment); * Preferred: Experience with MLOps and Computer Vision; * Passionate about problem-solving: approaches challenges intentionally, adheres to industry best practices, and considers long-term impacts of solutions; * Ability to collaborate effectively across diverse teams: fosters open, empathetic, and transparent dialogue to collectively deliver value; * Takes ownership of one’s career with constructive curiosity and proactive reasoning—driven to improve both self and the working environment. * Participate in structuring business problems and aligning them with technologies, statistical and mathematical modeling; * Plan, develop, and maintain machine learning and time series models; * Perform ETL (extraction, transformation, and validation) processes to support analytical development; * Support business teams in interpreting results and provide recommendations to improve processes; * Participate in the validation and implementation of developed models. 251204020218740775