• Automation of ETL processes in SQL and Python, for the creation of visuals in Tableau and Redash Dashboards (similar to Databricks) that enabled key insights for the improvement of the indicator and allowing to reduce the GMV Lost by products closed on the company’s website.• Building of data extraction pipelines, and analysis automations of the indicator that measures the percentage of customers with incomplete deliveries, generating actions that decreased 87% the percentage of affected customers, which represents higher GMV retention.• Responsible for increasing the savings in GMV of the products through the negotiation process, using analysis and automation of processes and based on priorities of products that represented the highest percentage of GMV within the company.• Development of an algorithm in Python that allows identifying the products that were no longer being sold on weekends, and reducing the percentage of waste from 10 tons to 2 tons of product per week.• Experience in project development using Storytelling techniques to present results with weekly and daily follow-ups for stakeholders, mainly using the agile SCRUM methodology for project monitoring and development.

• Implemented the automation of weekly payment checklists in order to reduce manual errors from the financial team. Using Google APIs and Python packages for data acquisition and manipulation, transforming them into important information for the project’s functioning, • I was able to reduce by zero the occurrence of manual errors in the payments • Assisted the team in making decisions by using data analysis with visualizations of graphs and tables. I leveraged Python libraries like pandas, seaborn, and data manipulation techniques to identify strategic delivery spots, which helped us achieve an average delivery time of less than 15 minutes, significantly reducing it from the initial 40 minutes. This success led to the project's approval for expansion across LATAM within just 3 months.

• Elaboration of a water balance (BH) simulation model for productivity calculation using the R Statistical software (R Language) to translate mathematical formulas into code language, resulting in an alternative way of calculating BH used in the Center for Research. • Contribution to the practice of versioning the codes developed in the group using Git, promoting organization, reducing conflicts, and improving the communication of the application development stage. • Replaced macros in VBA and manual tasks with automated data handling using Python and its main libraries (pandas and NumPy) for data acquisition and its respective transformation into essential information for the group, reducing the time needed for the execution of the process.

Elaboration of a computational mathematical model to answer how an environment influences the flight of bees using the R language, with statistical analysis of the results, which can help the field of beekeeping in decision making.

• Maintainance and software development using ColdFusion for building solutions to the costumer needs