Project Dineiros ● Increased the number of credit requests for Fintech Dineiros by 80% by implementing an API in Django to receive and approve said credits. ● Reduced manual review and data entry by 60% by implementing a custom dashboard for the Admin role.

● Reduced credit request time by 80% by implementing a new form in both FrontEnd and BackEnd.

● I increased from 10 to 500 documents processed with my ML pipeline implementation to process legal documents.

● I reduced by 90% the time of copying, file handling and manual input in 80 computers of the local network by implementing new GPOs and PowerShell and .bat scripts

Project SKEXIE (Skills and Experience Interpreter and Extractor) ● Augmented the amount of job offers processed from 100 to 2000 in a day by developing an API to interpret skills and experiences from external job posts using NLP (Natural Language Processing) to extract them to the platform’s format, deployed using AWS. ● Increased general processing of Job Offers by 60% with our custom pipeline implementation.

Reduced manual processing by 90% with an accuracy of 80% of Skills and Experience extracted.