**Description:** **To excel, you must demonstrate:** Bachelor's degree in Statistics, Mathematics, Engineering, Computer Science, Economics or related fields; Postgraduate or Master's degree in Data Science, AI or quantitative fields; Experience in data science and predictive analytics projects; Proficiency in Python programming (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch), SQL, relational and non-relational databases, Big Data with PySpark, Power BI, and AWS cloud environments; Knowledge of MLOps (MLflow, Airflow, CI/CD), Generative AI and LLMs, statistical, predictive and prescriptive modeling, NLP techniques, classification, regression and clustering, as well as best practices in versioning, documentation, data governance, and integration between data pipelines and corporate systems; Advanced knowledge of statistics, machine learning and data manipulation is desirable; Experience in industrial and corporate environments is a plus; Availability to work on-site in Belo Horizonte/MG Here’s how you’ll contribute to the Data Engineering team: **End-to-end leadership of data science projects:** defining the problem, collecting and processing data, modeling, validating and deploying, as well as developing and implementing Machine Learning, Generative AI and statistical models for forecasting, optimization, segmentation and recommendation; Designing data pipelines and analytical automations, ensuring process efficiency, quality and traceability, as well as building and maintaining strategic dashboards and executive reports to guarantee information consistency and reliability; Translating business area needs into analytical solutions with measurable impact on operational and financial outcomes, conducting exploratory analyses, correlation and causality studies to identify patterns, trends and opportunities; Supporting the definition and implementation of MLOps and model governance best practices, serving as a technical reference, promoting knowledge sharing and advancing the data team; Ensuring clear communication and storytelling of results for both technical and executive audiences, staying up to date with trends in data science, AI, and emerging tools and methodologies. 2512240202491812126