Gonzalo Argüello

This platform included not only the development of a web application but also mobile and desktop apps required to comply with local regulations regarding security protocols for digital signature. All these components interacted as an ecosystem that allowed organizations, of both private and public sectors, to convert many of its manual and paper-based procedures to more efficient digital processes.

My job, as the project leader, required me to manage and coordinate the development and support of the apps as well as be the technical leader in terms of security and regulatory requirements.

The largest financial company in Argentina, converting its business with the launch of several digital products, required a solution to include static (SAST) and dynamic (DAST) security analysis in all its development teams. I worked with POs and solution architects to align their processes to implement this tool while collecting new requirements that were discussed with the security team and then added as new features.

The big picture was a tool that executed DAST and SAST analysis triggered by GitLab CI pipelines whose results were displayed on a dashboard that each product team could use to manage their quality in terms of security. The technology stack included an API in Python Flask and Celery with a MongoDB and a front end based on Flask and Bootstrap. SAST was executed with Python scripts and DAST with a customized OWASP ZAP container.

The largest financial company in Argentina, converting its business with the launch of several digital products, was required to implement a solution to allow legacy and new users to authenticate through a unique point of access to an ecosystem of mobile and web applications.

The challenge was to implement a world-class SSO platform (Auth0) but also develop the necessary interfaces and pipelines behind the scene to transparently migrate more than 2 million users from its legacy databases and include specific onboarding processes to comply with the requirements of a digital wallet and eCommerce portal as well.

I lead a cross-functional team of developers, testers, and devops to build the software architecture that would support this migration while coordinating with the cloud infrastructure team and complying with security. The solution involved Auth0 with several extensions that expanded through AWS Lambdas and microservices in Node.js.

One of the most important beverage companies in the world requested a proof of concept to apply novel data analytics techniques to leverage its available data in order to increase sales through better-targeted campaigns.

I managed a small team of highly qualified data scientists during a four-month project at the client’s headquarters, which required the whole team to move from its home country to the US during this time period. Stakeholders were top-line managers, directors, and VPs looking for disruptive approaches to their usual way of understanding their market.

After analyzing datasets with over 1.3 billion records, the team produced a propensity model that allowed them to get valuable insights from data that enabled, among others, to identify the characteristics of potential consumers of new products (new launches) providing a whole new way of approaching marketing strategies.

Brazil's largest online marketplace (an Amazon-like platform, hereinafter "The Company") with millions of users (Sellers and Buyers) was facing increased financial costs derived from complex management of sellers’ billing accounts.

On payment days, The Company pays to the sellers those orders that have been shipped to its buyers, but there are chances that some of these orders get canceled after The Company has effectively made the payment to the seller, which derives in The Company needing to take note of each case and balancing the account in the next period, incurring in different adverse situations which meant additional costs such as refunding the buyer, legal fees for fraudulent on-time sellers, etc.

Our work was to analyze The Company’s historic data and build a predictive model that allowed them to anticipate many of these cases and reduce the financial cost derived from unbalanced operations.