Pedro Monastero

Led product strategy and across organization, establishing quarterly strategic planning based on market analysis, guaranteeing alignment between product and engineering teams, with regular touchpoints with the C-level.

Leader of the Risk Management Team and respective squads. Internalized all risk systems, reducing costs by 85%, increasing independency on vendors. Responsible for overseeing all operations related to user registration and transactional monitoring for fraud and chargeback prevention

Part of the founding team. Founded the risk and data teams from scratch, programming the all onboarding, KYC, transactions monitoring and antifraud systems (in Python), and later recruiting multiple teams to run the operation.

Responsible for fostering the digital wallet usage and growth through partnerships and credit incentives. Developed an automation (R lang) capable of optimizing acquisition cost by calculating the target customers list with highest chance of conversion, eliminating the need of a whole work day for an analyst.

The anti fraud platform started as an internal spinoff. I was part of the team that started the project and was responsible for the data science, fraud performance and control teams. They acted as a middle ground between operations and engineering, using models to automate decisions maximizing approval without chargebacks.

Created Products and Projects area for new product development and upselling opportunities. Successfully launched recurring payments product and integrated fraud prevention solution.

Sales executive responsible for the end to end of sales process. Developed automation system for commercial proposals, pricing, and contract documentation and that opened an opportunity to start the products and projects department.

Developed continuous improvement projects for Air Operations Control Center (CCOA). My main project was the creation of a statistical application for calculating ideal flight block times across all operated routes using a non-linear algorithm with statistical distributions for minimal error modeling