--> Fraud Prevention: Developed and deployed advanced machine learning models to significantly enhance platform security and user trust.--> Model Optimization: Led the consolidation of multiple models into a single, high-performing solution, resulting in a substantial increase in detection accuracy.--> Business-Driven Analytics: Collaborated closely with cross-functional teams to provide actionable insights and strategic recommendations, driving data-informed decision-making.--> Technical Leadership: Contributed to the development and implementation of best practices for model development and deployment, fostering a culture of innovation and excellence within the team.

- Data Scientist Role: development of machine learning models to prevent shipping fraud

- Coordination between Business, IT and Data Scientist teams for the analysis and implementation of models.- Performance analysis of Machine Learning models- Analysis, implementation and improvement of rules for Fraud detection with SQL, Python and Tableau- Responsible for migration to BigQuery

- Development of solutions in Python, such as Web Scrapping and automatically send reports to managers about main KPI's.- Data Analysis with SQL to perform daily tasks, and to support other teams with their needs.

- Modeling and monitoring data sets in Power BI- Analysis and processing of large volumes of data with SQL- Report creation in Power BI- Monitoring and updating of active models and reports

- Prepare oral lessons for the students (SQL and Excel)- Answer questions personally to each student