Luiz F.

GS1 Brasil is the non-profit that manages GS1 standards in Brazil, mainly product barcode identification.

• Led a team of four data scientists and two analysts.
• Improved the company’s data pipelines to enable near-real-time synchronization between production and analytics environments, even when processing large volumes of data.
• Led teams that developed new data-driven products for GS1 member companies.
• Managed internal and external stakeholders for market research projects while coordinating internal data processing and report generation teams.
• Applied machine learning to improve the quality and accuracy of market research data.

GS1 Brasil is the non-profit that manages GS1 standards in Brazil, mainly product barcode identification.

• Maintained and upgraded the company’s data lake and data pipelines, covering the full data lifecycle from ETL processes to reporting and machine learning solutions.
• Developed deep learning models using TensorFlow to measure and improve product data quality.
• Created dashboards in Power BI and Qlik Sense to support executives and business analysts in data-driven decision-making.
• Led a data quality project with a team of more than 10 members, automating monitoring and facilitating the management of product and location master data through web applications used by GS1 members.

Management Solutions is a Spanish business consulting company focused on regulated sectors, such as financial, telecom and energy.

• Developed an automated money laundering detection system using logistic regression in SAS, increasing the accuracy of bank compliance analysts by more than 70%.
• Led the team that developed client profitability models for a large telecommunications company using Hadoop/Spark for B2C and SQL Server for B2B, enabling analysts and executives to accurately assess the cost composition of both customer segments and individual customers.
• Developed a deep learning model to detect false retentions within the call center of a major telecommunications company, increasing the detection rate by more than 30%.
• Developed models to predict the impact of climate change on a telecommunications company’s costs under different projections, using geolocation data in Python, and built a Node.js frontend application to visualize the results.
• Developed an employee position and salary management system using the .NET Framework for a large telecommunications company, automating more than 60 work hours per month.