Feedzai Techblog

A showcase of JupyterLab’s powerful features in the life of data engineers, and the how it is used at Feedzai to unmask fraud.

We implemented support for AWS and GCP in the messaging library of the Feedzai platform. Read our findings.

Read what lessons we learned during the release process of Feedzai’s product documentation.

Learn more about active learning, a sub-field of machine learning.

Learn how to automatically detect sudden concept drift in a streaming data environment to produce insightful explanation reports.

Read on for the lessons I’ve learned by using 4 hours per week to learn & work on open-source at Feedzai.

This summer, we had our largest batch of summer interns ever! From over 200 applicants, we welcomed 15 interns across our 3 offices in…

Tips and tricks about using data science to build a product used by data scientists: the Product mindset.

Read about how we used graph visualization on transaction data to uncover fraudulent rings and discover the shape of fraud.

Have you ever wondered what a data scientist actually does? Let us explore what roles a data scientist can have. Part 1 of 3.

Learn how companies usually build their documentation team, and why they even do it in the first place.

A five-minute read on how mistakes shape our learning and why we should embrace them.

An insightful story about how product development matches users expectations.

The way of thinking we used to solve some of the CTF qualifiers challenges and a good intro for those curious about CTF challenges.

Part one of two