Felipe Almeida - Machine Learning Engineer

Felipe Almeida is responsible for engineering and managing Data Science & Machine Learning projects at Nubank. He has a Bachelor's degree in Computer Science and a Master's degree in Computer Engineering, both from UFRJ. Felipe has experience working with e-commerce, credit and fraud. Before joining Nubank in 2019, he worked in companies such as Itaú-Unibanco and VTEX. In his spare time, he likes to exercise and learn foreign languages. He is active on twitter and he blogs at https://queirozf.com

01 Sep 23

De-risking Real-time ML Projects: Addressing Common Failure Modes

In this post we list practices to substantially reduce the risk of failure in real-time machine learning projects.

27 Jun 23

Dealing with Train-serve Skew in Real-time ML Models: A Short Guide

A short guide explaining how to avoid and mitigate the impacts of train-serve skew in realtime ML models.

19 Dec 22

Automatic retraining for machine learning models: tips and lessons learned

In this post we'll go over some of the lessons we learned over the last years retraining models in an automatic fashion at Nubank.

05 Dec 22

Best Practices for Real-time Machine Learning: Alerting

In this article we analyze lessons learned and best practices assembled from years of applying Machine Learning to real-life problems at Nubank.

02 Sep 22

Acing the Data Science Interview: 8 Practical Tips with Examples

Practical tips to help you succeed in your next Data Science and/or Machine Learning interview

26 Apr 22

Data Scientist x Machine Learning Engineer Roles: How are they different? How are they alike?

Nubank's take on how these two roles interact and how each plays a key part in a successful team.

16 Aug 21

Machine Learning Model Monitoring – 9 Tips From the Trenches

Machine learning (ML) models are very sensitive pieces of software; their successful use needs careful monitoring to make sure they are working correctly.